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Advantages and Disadvantages of Artificial Intelligence

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Advantages and Disadvantages of Artificial Intelligence

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Artificial intelligence is one of the newest technologies that attempts to simulate human thinking.
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Advantages and Disadvantages of Artificial Intelligence

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Artificial Intelligence is one of the emerging technologies which tries to simulate human reasoning in AI systems. John McCarthy invented…

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Advantages and Disadvantages of Artificial Intelligence

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Advantages and Disadvantages of Artificial Intelligence

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Main idea:
Artificial intelligence is one of the newest technologies that attempts to simulate human thinking.

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- Ai eliminates human errors in projects
- It can do the most deadly tasks for humans
- It can help by doing the most repetitive jobs that make humans unhappy

Dialogue:
From my point of see very well explained positive points of view towards Ai in this article, which talks about how they could make our lifes better.

Summary:
Ai was first introduced in 1950 and it was the thought that a machine could perform thinking alike humans, and be unrecognizable from a human being. This concept coud be good for us since Ai's are also tireless which means they could do the most annoying jobs for us, allowing us to do fun things without having to worry about working boring jobs.

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# data[].attributes.attachment_link.title
Advantages and Disadvantages of Artificial Intelligence

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Artificial Intelligence is one of the emerging technologies which tries to simulate human reasoning in AI systems. John McCarthy invented…

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Main idea:
Artificial intelligence is one of the newest technologies that attempts to simulate human thinking.
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What is artificial intelligence (AI)?

Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.

How does AI work?

As the hype around AI has accelerated, vendors have been scrambling to promote how their products and services use it. Often, what they refer to as AI is simply a component of the technology, such as machine learning. AI requires a foundation of specialized hardware and software for writing and training machine learning algorithms. No single programming language is synonymous with AI, but Python, R, Java, C++ and Julia have features popular with AI developers.

In general, AI systems work by ingesting large amounts of labeled training data, analyzing the data for correlations and patterns, and using these patterns to make predictions about future states. In this way, a chatbot that is fed examples of text can learn to generate lifelike exchanges with people, or an image recognition tool can learn to identify and describe objects in images by reviewing millions of examples. New, rapidly improving generative AI techniques can create realistic text, images, music and other media.

AI programming focuses on cognitive skills that include the following:

Learning. This aspect of AI programming focuses on acquiring data and creating rules for how to turn it into actionable information. The rules, which are called algorithms, provide computing devices with step-by-step instructions for how to complete a specific task.

Reasoning. This aspect of AI programming focuses on choosing the right algorithm to reach a desired outcome.

Self-correction. This aspect of AI programming is designed to continually fine-tune algorithms and ensure they provide the most accurate results possible.

Creativity. This aspect of AIuses neural networks, rules-based systems, statistical methods and other AI techniques to generate new images, new text, new music and new ideas.

Why is artificial intelligence important?

AI is important for its potential to change how we live, work and play. It has been effectively used in business to automate tasks done by humans, including customer service work, lead generation, fraud detection and quality control. In a number of areas, AI can perform tasks much better than humans. Particularly when it comes to repetitive, detail-oriented tasks, such as analyzing large numbers of legal documents to ensure relevant fields are filled in properly, AI tools often complete jobs quickly and with relatively few errors. Because of the massive data sets it can process, AI can also give enterprises insights into their operations they might not have been aware of. The rapidly expanding population of generative AI tools will be important in fields ranging from education and marketing to product design.

Indeed, advances in AI techniques have not only helped fuel an explosion in efficiency, but opened the door to entirely new business opportunities for some larger enterprises. Prior to the current wave of AI, it would have been hard to imagine using computer software to connect riders to taxis, but Uber has become a Fortune 500 company by doing just that.

AI has become central to many of today's largest and most successful companies, including Alphabet, Apple, Microsoft and Meta, where AI technologies are used to improve operations and outpace competitors. At Alphabet subsidiary Google, for example, AI is central to its search engine, Waymo's self-driving cars and Google Brain, which invented the transformer neural network architecture that underpins the recent breakthroughs in natural language processing.

What are the advantages and disadvantages of artificial intelligence?

Artificial neural networks and deep learning AI technologies are quickly evolving, primarily because AI can process large amounts of data much faster and make predictions more accurately than humanly possible.

While the huge volume of data created on a daily basis would bury a human researcher, AI applications using machine learning can take that data and quickly turn it into actionable information. As of this writing, a primary disadvantage of AI is that it is expensive to process the large amounts of data AI programming requires. As AI techniques are incorporated into more products and services, organizations must also be attuned to AI's potential to create biased and discriminatory systems, intentionally or inadvertently.

Advantages of AI

The following are some advantages of AI.

Good at detail-oriented jobs. AI has proven to be as good or better than doctors at diagnosing certain cancers, including breast cancer and melanoma.

Reduced time for data-heavy tasks. AI is widely used in data-heavy industries, including banking and securities, pharma and insurance, to reduce the time it takes to analyze big data sets. Financial services, for example, routinely use AI to process loan applications and detect fraud.

Saves labor and increases productivity. An example here is the use of warehouse automation, which grew during the pandemic and is expected to increase with the integration of AI and machine learning.

Delivers consistent results. The best AI translation tools deliver high levels of consistency, offering even small businesses the ability to reach customers in their native language.

Can improve customer satisfaction through personalization. AI can personalize content, messaging, ads, recommendations and websites to individual customers.

AI-powered virtual agents are always available. AI programs do not need to sleep or take breaks, providing 24/7 service.

Disadvantages of AI

The following are some disadvantages of AI.

Expensive.

Requires deep technical expertise.

Limited supply of qualified workers to build AI tools.

Reflects the biases of its training data, at scale.

Lack of ability to generalize from one task to another.

Eliminates human jobs, increasing unemployment rates.

Strong AI vs. weak AI

AI can be categorized as weak or strong.

Weak AI, also known as narrow AI, is designed and trained to complete a specific task. Industrial robots and virtual personal assistants, such as Apple's Siri, use weak AI.

Strong AI, also known as artificial general intelligence (AGI), describes programming that can replicate the cognitive abilities of the human brain. When presented with an unfamiliar task, a strong AI system can use fuzzy logic to apply knowledge from one domain to another and find a solution autonomously. In theory, a strong AI program should be able to pass both a Turing test and the Chinese Room argument.

What are the 4 types of artificial intelligence?

Arend Hintze, an assistant professor of integrative biology and computer science and engineering at Michigan State University, explained that AI can be categorized into four types, beginning with the task-specific intelligent systems in wide use today and progressing to sentient systems, which do not yet exist. The categories are as follows.

Type 1: Reactive machines. These AI systems have no memory and are task-specific. An example is Deep Blue, the IBM chess program that beat Garry Kasparov in the 1990s. Deep Blue can identify pieces on a chessboard and make predictions, but because it has no memory, it cannot use past experiences to inform future ones.

Type 2: Limited memory. These AI systems have memory, so they can use past experiences to inform future decisions. Some of the decision-making functions in self-driving cars are designed this way.

Type 3: Theory of mind. Theory of mind is a psychology term. When applied to AI, it means the system would have the social intelligence to understand emotions. This type of AI will be able to infer human intentions and predict behavior, a necessary skill for AI systems to become integral members of human teams.

Type 4: Self-awareness. In this category, AI systems have a sense of self, which gives them consciousness. Machines with self-awareness understand their own current state. This type of AI does not yet exist.

What are examples of AI technology and how is it used today?

AI is incorporated into a variety of different types of technology. Here are seven examples.

Automation. When paired with AI technologies, automation tools can expand the volume and types of tasks performed. An example is robotic process automation ( RPA), a type of software that automates repetitive, rules-based data processing tasks traditionally done by humans. When combined with machine learning and emerging AI tools, RPA can automate bigger portions of enterprise jobs, enabling RPA's tactical bots to pass along intelligence from AI and respond to process changes.

Machine learning. This is the science of getting a computer to act without programming. Deep learning is a subset of machine learning that, in very simple terms, can be thought of as the automation of predictive analytics. There are three types of machine learning algorithms:

Supervised learning. Data sets are labeled so that patterns can be detected and used to label new data sets.

Unsupervised learning. Data sets aren't labeled and are sorted according to similarities or differences.

Reinforcement learning. Data sets aren't labeled but, after performing an action or several actions, the AI system is given feedback.

Machine vision. This technology gives a machine the ability to see. Machine vision captures and analyzes visual information using a camera, analog-to-digital conversion and digital signal processing. It is often compared to human eyesight, but machine vision isn't bound by biology and can be programmed to see through walls, for example. It is used in a range of applications from signature identification to medical image analysis. Computer vision, which is focused on machine-based image processing, is often conflated with machine vision.

Natural language processing (NLP). This is the processing of human language by a computer program. One of the older and best-known examples of NLP is spam detection, which looks at the subject line and text of an email and decides if it's junk. Current approaches to NLP are based on machine learning. NLP tasks include text translation, sentiment analysis and speech recognition.

Robotics. This field of engineering focuses on the design and manufacturing of robots. Robots are often used to perform tasks that are difficult for humans to perform or perform consistently. For example, robots are used in car production assembly lines or by NASA to move large objects in space. Researchers also use machine learning to build robots that can interact in social settings.

Self-driving cars. Autonomous vehicles use a combination of computer vision, image recognition and deep learning to build automated skills to pilot a vehicle while staying in a given lane and avoiding unexpected obstructions, such as pedestrians.

Text, image and audio generation. Generative AI techniques, which create various types of media from text prompts, are being applied extensively across businesses to create a seemingly limitless range of content types from photorealistic art to email responses and screenplays.

What are the applications of AI?

Artificial intelligence has made its way into a wide variety of markets. Here are 11 examples.

AI in healthcare. The biggest bets are on improving patient outcomes and reducing costs. Companies are applying machine learning to make better and faster medical diagnoses than humans. One of the best-known healthcare technologies is IBM Watson. It understands natural language and can respond to questions asked of it. The system mines patient data and other available data sources to form a hypothesis, which it then presents with a confidence scoring schema. Other AI applications include using online virtual health assistants and chatbots to help patients and healthcare customers find medical information, schedule appointments, understand the billing process and complete other administrative processes. An array of AI technologies is also being used to predict, fight and understand pandemics such as COVID-19.

AI in business. Machine learning algorithms are being integrated into analytics and customer relationship management ( CRM) platforms to uncover information on how to better serve customers. Chatbots have been incorporated into websites to provide immediate service to customers. The rapid advancement of generative AI technology such as ChatGPT is expected to have far-reaching consequences: eliminating jobs, revolutionizing product design and disrupting business models.

AI in education. AI can automate grading, giving educators more time for other tasks. It can assess students and adapt to their needs, helping them work at their own pace. AI tutors can provide additional support to students, ensuring they stay on track. The technology could also change where and how students learn, perhaps even replacing some teachers. As demonstrated by ChatGPT, Bard and other large language models, generative AI can help educators craft course work and other teaching materials and engage students in new ways. The advent of these tools also forces educators to rethink student homework and testing and revise policies on plagiarism.

AI in finance. AI in personal finance applications, such as Intuit Mint or TurboTax, is disrupting financial institutions. Applications such as these collect personal data and provide financial advice. Other programs, such as IBM Watson, have been applied to the process of buying a home. Today, artificial intelligence software performs much of the trading on Wall Street.

AI in law. The discovery process -- sifting through documents -- in law is often overwhelming for humans. Using AI to help automate the legal industry's labor-intensive processes is saving time and improving client service. Law firms use machine learning to describe data and predict outcomes, computer vision to classify and extract information from documents, and NLP to interpret requests for information.

AI in entertainment and media. The entertainment business uses AI techniques for targeted advertising, recommending content, distribution, detecting fraud, creating scripts and making movies. Automated journalism helps newsrooms streamline media workflows reducing time, costs and complexity. Newsrooms use AI to automate routine tasks, such as data entry and proofreading; and to research topics and assist with headlines. How journalism can reliably use ChatGPT and other generative AI to generate content is open to question.

AI in software coding and IT processes. New generative AI tools can be used to produce application code based on natural language prompts, but it is early days for these tools and unlikely they will replace software engineers soon. AI is also being used to automate many IT processes, including data entry, fraud detection, customer service, and predictive maintenance and security.

Security. AI and machine learning are at the top of the buzzword list security vendors use to market their products, so buyers should approach with caution. Still, AI techniques are being successfully applied to multiple aspects of cybersecurity, including anomaly detection, solving the false-positive problem and conducting behavioral threat analytics. Organizations use machine learning in security information and event management ( SIEM) software and related areas to detect anomalies and identify suspicious activities that indicate threats. By analyzing data and using logic to identify similarities to known malicious code, AI can provide alerts to new and emerging attacks much sooner than human employees and previous technology iterations.

AI in manufacturing. Manufacturing has been at the forefront of incorporating robots into the workflow. For example, the industrial robots that were at one time programmed to perform single tasks and separated from human workers, increasingly function as cobots: Smaller, multitasking robots that collaborate with humans and take on responsibility for more parts of the job in warehouses, factory floors and other workspaces.

AI in banking. Banks are successfully employing chatbots to make their customers aware of services and offerings and to handle transactions that don't require human intervention. AI virtual assistants are used to improve and cut the costs of compliance with banking regulations. Banking organizations use AI to improve their decision-making for loans, set credit limits and identify investment opportunities.

AI in transportation. In addition to AI's fundamental role in operating autonomous vehicles, AI technologies are used in transportation to manage traffic, predict flight delays, and make ocean shipping safer and more efficient. In supply chains, AI is replacing traditional methods of forecasting demand and predicting disruptions, a trend accelerated by COVID-19 when many companies were caught off guard by the effects of a global pandemic on the supply and demand of goods.

Augmented intelligence vs. artificial intelligence

Some industry experts have argued that the term artificial intelligence is too closely linked to popular culture, which has caused the general public to have improbable expectations about how AI will change the workplace and life in general. They have suggested using the term augmented intelligence to differentiate between AI systems that act autonomously -- popular culture examples include Hal 9000 and The Terminator -- and AI tools that support humans.

Augmented intelligence. Some researchers and marketers hope the label augmented intelligence, which has a more neutral connotation, will help people understand that most implementations of AI will be weak and simply improve products and services. Examples include automatically surfacing important information in business intelligence reports or highlighting important information in legal filings. The rapid adoption of ChatGPT and Bard across industry indicates a willingness to use AI to support human decision-making.

Artificial intelligence. True AI, or AGI, is closely associated with the concept of the technological singularity -- a future ruled by an artificial superintelligence that far surpasses the human brain's ability to understand it or how it is shaping our reality. This remains within the realm of science fiction, though some developers are working on the problem. Many believe that technologies such as quantum computing could play an important role in making AGI a reality and that we should reserve the use of the term AI for this kind of general intelligence.

Ethical use of artificial intelligence

While AI tools present a range of new functionality for businesses, the use of AI also raises ethical questions because, for better or worse, an AI system will reinforce what it has already learned.

This can be problematic because machine learning algorithms, which underpin many of the most advanced AI tools, are only as smart as the data they are given in training. Because a human being selects what data is used to train an AI program, the potential for machine learning bias is inherent and must be monitored closely.

Anyone looking to use machine learning as part of real-world, in-production systems needs to factor ethics into their AI training processes and strive to avoid bias. This is especially true when using AI algorithms that are inherently unexplainable in deep learning and generative adversarial network ( GAN) applications.

Explainability is a potential stumbling block to using AI in industries that operate under strict regulatory compliance requirements. For example, financial institutions in the United States operate under regulations that require them to explain their credit-issuing decisions. When a decision to refuse credit is made by AI programming, however, it can be difficult to explain how the decision was arrived at because the AI tools used to make such decisions operate by teasing out subtle correlations between thousands of variables. When the decision-making process cannot be explained, the program may be referred to as black box AI.

In summary, AI's ethical challenges include the following: bias, due to improperly trained algorithms and human bias; misuse, due to deepfakes and phishing; legal concerns, including AI libel and copyright issues; elimination of jobs; and data privacy concerns, particularly in the banking, healthcare and legal fields.

AI governance and regulations

Despite potential risks, there are currently few regulations governing the use of AI tools, and where laws do exist, they typically pertain to AI indirectly. For example, as previously mentioned, U.S. Fair Lending regulations require financial institutions to explain credit decisions to potential customers. This limits the extent to which lenders can use deep learning algorithms, which by their nature are opaque and lack explainability.

The European Union's General Data Protection Regulation ( GDPR) is considering AI regulations. GDPR's strict limits on how enterprises can use consumer data already limits the training and functionality of many consumer-facing AI applications.

Policymakers in the U.S. have yet to issue AI legislation, but that could change soon. A "Blueprint for an AI Bill of Rights" published in October 2022 by the White House Office of Science and Technology Policy (OSTP) guides businesses on how to implement ethical AI systems. The U.S. Chamber of Commerce also called for AI regulations in a report released in March 2023.

Crafting laws to regulate AI will not be easy, in part because AI comprises a variety of technologies that companies use for different ends, and partly because regulations can come at the cost of AI progress and development. The rapid evolution of AI technologies is another obstacle to forming meaningful regulation of AI, as are the challenges presented by AI's lack of transparency that make it difficult to see how the algorithms reach their results. Moreover, technology breakthroughs and novel applications such as ChatGPT and Dall-E can make existing laws instantly obsolete. And, of course, the laws that governments do manage to craft to regulate AI don't stop criminals from using the technology with malicious intent.

What is the history of AI?

The concept of inanimate objects endowed with intelligence has been around since ancient times. The Greek god Hephaestus was depicted in myths as forging robot-like servants out of gold. Engineers in ancient Egypt built statues of gods animated by priests. Throughout the centuries, thinkers from Aristotle to the 13th century Spanish theologian Ramon Llull to René Descartes and Thomas Bayes used the tools and logic of their times to describe human thought processes as symbols, laying the foundation for AI concepts such as general knowledge representation.

The late 19th and first half of the 20th centuries brought forth the foundational work that would give rise to the modern computer. In 1836, Cambridge University mathematician Charles Babbage and Augusta Ada King, Countess of Lovelace, invented the first design for a programmable machine.

1940s. Princeton mathematician John Von Neumann conceived the architecture for the stored-program computer -- the idea that a computer's program and the data it processes can be kept in the computer's memory. And Warren McCulloch and Walter Pitts laid the foundation for neural networks.

1950s. With the advent of modern computers, scientists could test their ideas about machine intelligence. One method for determining whether a computer has intelligence was devised by the British mathematician and World War II code-breaker Alan Turing. The Turing test focused on a computer's ability to fool interrogators into believing its responses to their questions were made by a human being.

1956. The modern field of artificial intelligence is widely cited as starting this year during a summer conference at Dartmouth College. Sponsored by the Defense Advanced Research Projects Agency (DARPA), the conference was attended by 10 luminaries in the field, including AI pioneers Marvin Minsky, Oliver Selfridge and John McCarthy, who is credited with coining the term artificial intelligence. Also in attendance were Allen Newell, a computer scientist, and Herbert A. Simon, an economist, political scientist and cognitive psychologist. The two presented their groundbreaking Logic Theorist, a computer program capable of proving certain mathematical theorems and referred to as the first AI program.

1950s and 1960s. In the wake of the Dartmouth College conference, leaders in the fledgling field of AI predicted that a man-made intelligence equivalent to the human brain was around the corner, attracting major government and industry support. Indeed, nearly 20 years of well-funded basic research generated significant advances in AI: For example, in the late 1950s, Newell and Simon published the General Problem Solver (GPS) algorithm, which fell short of solving complex problems but laid the foundations for developing more sophisticated cognitive architectures; and McCarthy developed Lisp, a language for AI programming still used today. In the mid-1960s, MIT Professor Joseph Weizenbaum developed ELIZA, an early NLP program that laid the foundation for today's chatbots.

1970s and 1980s. The achievement of artificial general intelligence proved elusive, not imminent, hampered by limitations in computer processing and memory and by the complexity of the problem. Government and corporations backed away from their support of AI research, leading to a fallow period lasting from 1974 to 1980 known as the first " AI Winter." In the 1980s, research on deep learning techniques and industry's adoption of Edward Feigenbaum's expert systems sparked a new wave of AI enthusiasm, only to be followed by another collapse of government funding and industry support. The second AI winter lasted until the mid-1990s.

1990s. Increases in computational power and an explosion of data sparked an AI renaissance in the late 1990s that set the stage for the remarkable advances in AI we see today. The combination of big data and increased computational power propelled breakthroughs in NLP, computer vision, robotics, machine learning and deep learning. In 1997, as advances in AI accelerated, IBM's Deep Blue defeated Russian chess grandmaster Garry Kasparov, becoming the first computer program to beat a world chess champion.

2000s. Further advances in machine learning, deep learning, NLP, speech recognition and computer vision gave rise to products and services that have shaped the way we live today. These include the 2000 launch of Google's search engine and the 2001 launch of Amazon's recommendation engine. Netflix developed its recommendation system for movies, Facebook introduced its facial recognition system and Microsoft launched its speech recognition system for transcribing speech into text. IBM launched Watson and Google started its self-driving initiative, Waymo.

2010s. The decade between 2010 and 2020 saw a steady stream of AI developments. These include the launch of Apple's Siri and Amazon's Alexa voice assistants; IBM Watson's victories on Jeopardy; self-driving cars; the development of the first generative adversarial network; the launch of TensorFlow, Google's open source deep learning framework; the founding of research lab OpenAI, developers of the GPT-3 language model and Dall-E image generator; the defeat of world Go champion Lee Sedol by Google DeepMind's AlphaGo; and the implementation of AI-based systems that detect cancers with a high degree of accuracy.

2020s. The current decade has seen the advent of generative AI, a type of artificial intelligence technology that can produce new content. Generative AI starts with a prompt that could be in the form of a text, an image, a video, a design, musical notes or any input that the AI system can process. Various AI algorithms then return new content in response to the prompt. Content can include essays, solutions to problems, or realistic fakes created from pictures or audio of a person. The abilities of language models such as ChatGPT-3, Google's Bard and Microsoft's Megatron-Turing NLG have wowed the world, but the technology is still in early stages, as evidenced by its tendency to hallucinate or skew answers.

AI tools and services

AI tools and services are evolving at a rapid rate. Current innovations in AI tools and services can be traced to the 2012 AlexNet neural network that ushered in a new era of high-performance AI built on GPUs and large data sets. The key change was the ability to train neural networks on massive amounts of data across multiple GPU cores in parallel in a more scalable way.

Over the last several years, the symbiotic relationship between AI discoveries at Google, Microsoft, and OpenAI, and the hardware innovations pioneered by Nvidia have enabled running ever-larger AI models on more connected GPUs, driving game-changing improvements in performance and scalability.

The collaboration among these AI luminaries was crucial for the recent success of ChatGPT, not to mention dozens of other breakout AI services. Here is a rundown of important innovations in AI tools and services.

Transformers. Google, for example, led the way in finding a more efficient process for provisioning AI training across a large cluster of commodity PCs with GPUs. This paved the way for the discovery of transformers that automate many aspects of training AI on unlabeled data.

Hardware optimization. Just as important, hardware vendors like Nvidia are also optimizing the microcode for running across multiple GPU cores in parallel for the most popular algorithms. Nvidia claimed the combination of faster hardware, more efficient AI algorithms, fine-tuning GPU instructions and better data center integration is driving a million-fold improvement in AI performance. Nvidia is also working with all cloud center providers to make this capability more accessible as AI-as-a-Service through IaaS, SaaS and PaaS models.

Generative pre-trained transformers. The AI stack has also evolved rapidly over the last few years. Previously enterprises would have to train their AI models from scratch. Increasingly vendors such as OpenAI, Nvidia, Microsoft, Google, and others provide generative pre-trained transformers (GPTs), which can be fine-tuned for a specific task at a dramatically reduced cost, expertise and time. Whereas some of the largest models are estimated to cost $5 million to $10 million per run, enterprises can fine-tune the resulting models for a few thousand dollars. This results in faster time to market and reduces risk.

AI cloud services. Among the biggest roadblocks that prevent enterprises from effectively using AI in their businesses are the data engineering and data science tasks required to weave AI capabilities into new apps or to develop new ones. All the leading cloud providers are rolling out their own branded AI as service offerings to streamline data prep, model development and application deployment. Top examples include AWS AI Services, Google Cloud AI, Microsoft Azure AI platform, IBM AI solutions and Oracle Cloud Infrastructure AI Services.

Cutting-edge AI models as a service. Leading AI model developers also offer cutting-edge AI models on top of these cloud services. OpenAI has dozens of large language models optimized for chat, NLP, image generation and code generation that are provisioned through Azure. Nvidia has pursued a more cloud-agnostic approach by selling AI infrastructure and foundational models optimized for text, images and medical data available across all cloud providers. Hundreds of other players are offering models customized for various industries and use cases as well.
George Lawton also contributed to this article.

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What is Artificial Intelligence and How Does AI Work? TechTarget

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Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. Read the full definition.

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Explore the Pros & Cons of Artificial Intelligence & know about its positive & negative aspects. AI advantages & disadvantages are explained with examples for better understanding.

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Pros and Cons of Artificial Intelligence - A Threat or a Blessing? - DataFlair

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Explore the Pros & Cons of Artificial Intelligence & know about its positive & negative aspects. AI advantages & disadvantages are explained with examples for better understanding.

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Not losing our creative jobs and not worrying about deciding ethical dilemmas.

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-Lacks creativity
-Reduces employment
-Ethical dilemmas

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From my point of view, the article explains very well the negative part of AI, and why is very unethical to create them.

Summary:
Some uses of AI are unlikely to impact human jobs. That frees up human workers to do work that offers more ability for creative thinking. But it doesn't mean we shouldn't look to use AI, but it's important that we understand its limitations so that we can implement it effectively.

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(Photo by Andreas SOLARO / AFP) (Photo by ANDREAS SOLARO/AFP via Getty Images)
AFP via Getty Images

Key takeaways

Artificial intelligence (AI) is hitting the mainstream, though the first form of AI was invented in England, way back in 1951.

Nowadays AI is used in a wide range of applications, from our personal assistants like Alexa and Siri, to cars, factories and healthcare.

AI has the power to make massive improvements to our quality of life, but it's not perfect.

Artificial intelligence, or AI, is everywhere right now. In truth, the fundamentals of AI and machine learning have been around for a long time. The first primitive form of AI was an automated checkers bot which was created by Cristopher Strachey from the University of Manchester, England, back in 1951.

It's come a long way since then, and we're starting to see a large number of high profile use cases for the technology being thrust into the mainstream.

Some of the hottest applications of AI include the development of autonomous vehicles, facial recognition software, virtual assistants like Amazon's Alexa and Apple's Siri and a huge array of industrial applications in all industries from farming to gaming to healthcare.

And of course, there's our AI-powered investing app, Q.ai.

But with this massive increase in the use of AI in our everyday lives, and algorithms that are constantly improving, what are the pros and cons of this powerful technology? Is it a force for good, for evil or somewhere in between?
Download Q.ai today for access to AI-powered investment strategies.
The Pros of AI

There's no denying there are a lot of benefits to using AI. There's a reason it's becoming so popular, and that's because the technology in many ways makes our lives better and/or easier.

Fewer errors

Humans are great. Really, we're awesome. But we're not perfect. After a few hours in front of a computer screen, we can get a little tired, a little sloppy. It's nothing that some lunch, a coffee and a lap around the block won't fix, but it happens.

Even if we're fresh at the start of the day, we might be a bit distracted by what's going on at home. Maybe we're going through a bad breakup, or our football team lost last night, or someone cut us off in traffic on the way into work.

Whatever the reason, it's common and normal for human attention to move in and out.

These lapses of attention can lead to mistakes. Typing the wrong number in a mathematical equation, missing out a line of code or in the case of heavy duty workplaces like factories, bigger mistakes which can lead to injury, or even death.

24/7 Uptime

Speaking of tiredness, AI doesn't suffer from sugar crashes or need a caffeine pick-me-up to get through the 3pm slump. As long as the power is turned on, algorithms can run 24 hours a day, 7 days a week without needing a break.

Not only can an AI program run constantly, but it also runs consistently. It will do the same tasks, to the same standard, forever.

For repetitive tasks this makes them a far better employee than a human. It leads to fewer errors, less downtime and a higher level of safety. They're all big pros in our book.

Analyze large sets of data - fast

This is a big one for us here at Q.ai. Humans simply can't match AI when it comes to analyzing large datasets. For a human to go through 10,000 lines of data on a spreadsheet would take days, if not weeks.

AI can do it in a matter of minutes.

A properly trained machine learning algorithm can analyze massive amounts of data in a shockingly small amount of time. We use this capability extensively in our Investment Kits, with our AI looking at a wide range of historical stock and market performance and volatility data, and comparing this to other data such as interest rates, oil prices and more.

AI can then pick up patterns in the data and offer predictions for what might happen in the future. It's a powerful application that has huge real world implications. From an investment management standpoint, it's a game-changer.

The Cons of AI

But it's not all roses. Obviously there are certain downsides to using AI and machine learning to complete tasks. It doesn't mean we shouldn't look to use AI, but it's important that we understand its limitations so that we can implement it in the right way.

Lacks creativity

AI bases its decisions on what has happened in the past. By definition then, it's not well suited to coming up with new or innovative ways to look at problems or situations. Now in many ways, the past is a very good guide as to what might happen in the future, but it isn't going to be perfect.

There's always the potential for a never-before-seen variable which sits outside the range of expected outcomes.

Because of this, AI works very well for doing the 'grunt work' while keeping the overall strategy decisions and ideas to the human mind.

From an investment perspective, the way we implement this is by having our financial analysts come up with an investment thesis and strategy, and then have our AI take care of the implementation of that strategy.

We still need to tell our AI which datasets to look at in order to get the desired outcome for our clients. We can't simply say "go generate returns." We need to provide an investment universe for the AI to look at, and then give parameters on which data points make a 'good' investment within the given strategy.

Reduces employment

We're on the fence about this one, but it's probably fair to include it because it's a common argument against the use of AI.

Some uses of AI are unlikely to impact human jobs. For example, the image processing AI in new cars which allows for automatic braking in the event of a potential crash. That's not replacing a job.

An AI-powered robot assembling those cars in the factory, that probably is taking the place of a human.

The important point to keep in mind is that AI in its current iteration is aiming to replace dangerous and repetitive work. That frees up human workers to do work which offers more ability for creative thinking, which is likely to be more fulfilling.

AI technology is also going to allow for the invention and many aids which will help workers be more efficient in the work that they do. All in all, we believe that AI is a positive for the human workforce in the long run, but that's not to say there won't be some growing pains in between.

Ethical dilemmas

AI is purely logical. It makes decisions based on preset parameters that leave little room for nuance and emotion. In many cases this is a positive, as these fixed rules are part of what allows it to analyze and predict huge amounts of data.

In turn though, it makes it very difficult to incorporate areas such as ethics and morality into the algorithm. The output of the algorithm is only as good as the parameters which its creators set, meaning there is room for potential bias within the AI itself.

Imagine, for example, the case of an autonomous vehicle, which gets into a potential road traffic accident situation, where it must choose between driving off a cliff or hitting a pedestrian. As a human driver in that situation, our instincts will take over. Those instincts will be based on our own personal background and history, with no time for conscious thought on the best course of action.

For AI, that decision will be a logical one based on what the algorithm has been programmed to do in an emergency situation. It's easy to see how this can become a very challenging problem to address.

How to use AI for your personal wealth creation

We use AI in all of our Investment Kits, to analyze, predict and rebalance on a regular basis. A great example is our Global Trends Kit, which uses AI and machine learning to predict the risk-adjusted performance of a range of different asset classes over the coming week.

These asset classes include stocks and bonds, emerging markets, forex, oil, gold and even the volatility index (VIX).

Our algorithm makes the predictions each week and then automatically rebalances the portfolio on what it believes to be the best mix of risk and return based on a huge amount of historical data.

Investors can take the AI a step further by implementing Portfolio Protection. This uses a different machine learning algorithm to analyze the sensitivity of the portfolio to various forms of risk, such as oil risk, interest rate risk and overall market risk. It then automatically implements sophisticated hedging strategies which aim to reduce the downside risk of the portfolio.
Download Q.ai today for access to AI-powered investment strategies.
If you believe in the power of AI and want to harness it for your financial future, Q.ai has got you covered.

# data[].attributes.attachment_link.authors[].name
Q.ai - Powering a Personal Wealth Movement

# data[].attributes.attachment_link.title
The Pros And Cons Of Artificial Intelligence

# data[].attributes.attachment_link.description
Artificial intelligence (AI) is hitting the mainstream, though the first form of AI was invented in England, way back in 1951. Nowadays AI is used in a wide range of applications, from our personal assistants like Alexa and Siri, to cars, factories and healthcare.

# data[].attributes.body
Main idea:
To have fewer errors and more effectiveness in work all the time.
25
Arguments:
-Fewer errors
-24/7 Uptime
-Analyze large sets of data - fast
Dialogue:
From my point of view, the article explains very well the positive part of AI, and why they could work out better.

Summary:
There's a reason why AI is so popular - it makes our lives better and or easier in many ways. A properly trained machine learning algorithm can analyze massive amounts of data in a shockingly small amount of time. As long as the power is turned on, algorithms can run 24 hours a day, 7 days a week without needing a break. It will do the same tasks, to the same standard, forever.

# data[].attributes.attachment_link.readable_text
(Photo by Andreas SOLARO / AFP) (Photo by ANDREAS SOLARO/AFP via Getty Images)
AFP via Getty Images

Key takeaways

Artificial intelligence (AI) is hitting the mainstream, though the first form of AI was invented in England, way back in 1951.

Nowadays AI is used in a wide range of applications, from our personal assistants like Alexa and Siri, to cars, factories and healthcare.

AI has the power to make massive improvements to our quality of life, but it's not perfect.

Artificial intelligence, or AI, is everywhere right now. In truth, the fundamentals of AI and machine learning have been around for a long time. The first primitive form of AI was an automated checkers bot which was created by Cristopher Strachey from the University of Manchester, England, back in 1951.

It's come a long way since then, and we're starting to see a large number of high profile use cases for the technology being thrust into the mainstream.

Some of the hottest applications of AI include the development of autonomous vehicles, facial recognition software, virtual assistants like Amazon's Alexa and Apple's Siri and a huge array of industrial applications in all industries from farming to gaming to healthcare.

And of course, there's our AI-powered investing app, Q.ai.

But with this massive increase in the use of AI in our everyday lives, and algorithms that are constantly improving, what are the pros and cons of this powerful technology? Is it a force for good, for evil or somewhere in between?
Download Q.ai today for access to AI-powered investment strategies.
The Pros of AI

There's no denying there are a lot of benefits to using AI. There's a reason it's becoming so popular, and that's because the technology in many ways makes our lives better and/or easier.

Fewer errors

Humans are great. Really, we're awesome. But we're not perfect. After a few hours in front of a computer screen, we can get a little tired, a little sloppy. It's nothing that some lunch, a coffee and a lap around the block won't fix, but it happens.

Even if we're fresh at the start of the day, we might be a bit distracted by what's going on at home. Maybe we're going through a bad breakup, or our football team lost last night, or someone cut us off in traffic on the way into work.

Whatever the reason, it's common and normal for human attention to move in and out.

These lapses of attention can lead to mistakes. Typing the wrong number in a mathematical equation, missing out a line of code or in the case of heavy duty workplaces like factories, bigger mistakes which can lead to injury, or even death.

24/7 Uptime

Speaking of tiredness, AI doesn't suffer from sugar crashes or need a caffeine pick-me-up to get through the 3pm slump. As long as the power is turned on, algorithms can run 24 hours a day, 7 days a week without needing a break.

Not only can an AI program run constantly, but it also runs consistently. It will do the same tasks, to the same standard, forever.

For repetitive tasks this makes them a far better employee than a human. It leads to fewer errors, less downtime and a higher level of safety. They're all big pros in our book.

Analyze large sets of data - fast

This is a big one for us here at Q.ai. Humans simply can't match AI when it comes to analyzing large datasets. For a human to go through 10,000 lines of data on a spreadsheet would take days, if not weeks.

AI can do it in a matter of minutes.

A properly trained machine learning algorithm can analyze massive amounts of data in a shockingly small amount of time. We use this capability extensively in our Investment Kits, with our AI looking at a wide range of historical stock and market performance and volatility data, and comparing this to other data such as interest rates, oil prices and more.

AI can then pick up patterns in the data and offer predictions for what might happen in the future. It's a powerful application that has huge real world implications. From an investment management standpoint, it's a game-changer.

The Cons of AI

But it's not all roses. Obviously there are certain downsides to using AI and machine learning to complete tasks. It doesn't mean we shouldn't look to use AI, but it's important that we understand its limitations so that we can implement it in the right way.

Lacks creativity

AI bases its decisions on what has happened in the past. By definition then, it's not well suited to coming up with new or innovative ways to look at problems or situations. Now in many ways, the past is a very good guide as to what might happen in the future, but it isn't going to be perfect.

There's always the potential for a never-before-seen variable which sits outside the range of expected outcomes.

Because of this, AI works very well for doing the 'grunt work' while keeping the overall strategy decisions and ideas to the human mind.

From an investment perspective, the way we implement this is by having our financial analysts come up with an investment thesis and strategy, and then have our AI take care of the implementation of that strategy.

We still need to tell our AI which datasets to look at in order to get the desired outcome for our clients. We can't simply say "go generate returns." We need to provide an investment universe for the AI to look at, and then give parameters on which data points make a 'good' investment within the given strategy.

Reduces employment

We're on the fence about this one, but it's probably fair to include it because it's a common argument against the use of AI.

Some uses of AI are unlikely to impact human jobs. For example, the image processing AI in new cars which allows for automatic braking in the event of a potential crash. That's not replacing a job.

An AI-powered robot assembling those cars in the factory, that probably is taking the place of a human.

The important point to keep in mind is that AI in its current iteration is aiming to replace dangerous and repetitive work. That frees up human workers to do work which offers more ability for creative thinking, which is likely to be more fulfilling.

AI technology is also going to allow for the invention and many aids which will help workers be more efficient in the work that they do. All in all, we believe that AI is a positive for the human workforce in the long run, but that's not to say there won't be some growing pains in between.

Ethical dilemmas

AI is purely logical. It makes decisions based on preset parameters that leave little room for nuance and emotion. In many cases this is a positive, as these fixed rules are part of what allows it to analyze and predict huge amounts of data.

In turn though, it makes it very difficult to incorporate areas such as ethics and morality into the algorithm. The output of the algorithm is only as good as the parameters which its creators set, meaning there is room for potential bias within the AI itself.

Imagine, for example, the case of an autonomous vehicle, which gets into a potential road traffic accident situation, where it must choose between driving off a cliff or hitting a pedestrian. As a human driver in that situation, our instincts will take over. Those instincts will be based on our own personal background and history, with no time for conscious thought on the best course of action.

For AI, that decision will be a logical one based on what the algorithm has been programmed to do in an emergency situation. It's easy to see how this can become a very challenging problem to address.

How to use AI for your personal wealth creation

We use AI in all of our Investment Kits, to analyze, predict and rebalance on a regular basis. A great example is our Global Trends Kit, which uses AI and machine learning to predict the risk-adjusted performance of a range of different asset classes over the coming week.

These asset classes include stocks and bonds, emerging markets, forex, oil, gold and even the volatility index (VIX).

Our algorithm makes the predictions each week and then automatically rebalances the portfolio on what it believes to be the best mix of risk and return based on a huge amount of historical data.

Investors can take the AI a step further by implementing Portfolio Protection. This uses a different machine learning algorithm to analyze the sensitivity of the portfolio to various forms of risk, such as oil risk, interest rate risk and overall market risk. It then automatically implements sophisticated hedging strategies which aim to reduce the downside risk of the portfolio.
Download Q.ai today for access to AI-powered investment strategies.
If you believe in the power of AI and want to harness it for your financial future, Q.ai has got you covered.

# data[].attributes.attachment_link.authors[].name
Q.ai - Powering a Personal Wealth Movement

# data[].attributes.attachment_link.title
The Pros And Cons Of Artificial Intelligence

# data[].attributes.attachment_link.description
Artificial intelligence (AI) is hitting the mainstream, though the first form of AI was invented in England, way back in 1951. Nowadays AI is used in a wide range of applications, from our personal assistants like Alexa and Siri, to cars, factories and healthcare.

# data[].attributes.body
ARTIFICIAL INTELLIGENCE

Main Idea:

Artificial Intelligence is the ability of a digital computer or computer-controlled robot, to perform any common task in our daily life.

Arguments/Facts:

1. Psychologists generally do not characterize human intelligence by just one quality but by the combination of many abilities.

2. There has been considerable success in programming computers to draw inferences, especially deductive inferences.

3. Artificial intelligence was done in the mid-20th century by the British logician and computer settler Alan Mathison Turing.

Dialogue

In my opinion, this article explains perfectly all the aspects of AI, and how affects us from a moral, and scientific point of view. It also it's very informative and gives very useful and interesting things about the topic.

Summary:
Artificial intelligence is the ability of a digital computer or computer-controlled robot to perform tasks.
Since the development of the digital computer in the 1940s, it has been shown that computers can be programmed to carry out very complex tasks.
On the other hand, some programs have reached the performance levels of human experts and professionals in performing certain specific tasks, so artificial intelligence in this limited sense is found in applications as diverse as medical diagnosis, computer search engines, and voice or handwriting recognition.

APPA:
Britannica School. (s. f.). https://school.eb.com/?target=%2Flevels%2Fhigh%2Farticle%2Fartificial-intelligence%2F9711

# data[].attributes.attachment_link.description
Welcome to Britannica School, a safe, up-to-date, and age-appropriate information resource for Elementary, Middle, and High School.

# data[].attributes.body
Main idea:
Artificial Inteligence are machines that have incorporated with human-like intelligence to perform tasks as we do. This intelligence is made by comple algorithms and mathematical functions
Arguments/facts:
1. Ai is everywhere, in cars, phones, social media feeds, videogames, banking, surveillance, and many other aspects of our daily life.
2. Our robots uses the given input and finds the solution for a problem
3. AI provides machines with the capability to adapt reason and provide solutions.
4. Two types of AI are classified into Weak AI focuses solely on one task. Strong AI, this types of robots that only exisits in fiction stories, movies...

Dialogue:
In my point of view this video, explains perfectly every single part of AI. It's very interesting how the video is divided into four blocs, helping us to understand better all single parts of the video.

Summary:
Artificial intelligence is machines that have incorporated human-like intelligence to perform tasks as we do.
Ai is everywhere, in cars, phones, social media, video games, banking, surveillance, and many other aspects of our daily lives.
AI gives machines the ability to adapt reason and provide solutions.
Two types of AI are classified as weak AI that focuses solely on one task. Strong AI, this kind of robot that only exists in fictional stories, movies...

APPA:
Simplilearn. (2019, 30 abril). What Is Artificial Intelligence? | 🔥Artificial Intelligence Course | AI In 5 Minutes | |Simplilearn. YouTube. https://www.youtube.com/watch?v=ad79nYk2keg

# data[].attributes.attachment_link.title
What Is AI? | Artificial Intelligence | What is Artificial Intelligence? | AI In 5 Mins |Simplilearn

# data[].attributes.body
Main Idea:

Arguments:
-Learning
-Reasoning
-Perception

Dialogue:
In my opinion, this article explains perfectly all the aspects of AI, and how affects us from a scientific point of view.

Summary:
Despite advances in computer processing speed and memory capacity, there are as yet no programs that can match human flexibility. One of the earliest systems to integrate perception and action was FREDDY, a stationary robot with a moving television eye and pincer hand. Although none of these programs actually understands language, they may eventually reach the point where their command of a language is indistinguishable from that of a normal human.

# data[].attributes.attachment_link.readable_text
What is artificial intelligence?

Are artificial intelligence and machine learning the same?

artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. Since the development of the digital computer in the 1940s, it has been demonstrated that computers can be programmed to carry out very complex tasks-such as discovering proofs for mathematical theorems or playing chess-with great proficiency. Still, despite continuing advances in computer processing speed and memory capacity, there are as yet no programs that can match full human flexibility over wider domains or in tasks requiring much everyday knowledge. On the other hand, some programs have attained the performance levels of human experts and professionals in performing certain specific tasks, so that artificial intelligence in this limited sense is found in applications as diverse as medical diagnosis, computer search engines, voice or handwriting recognition, and chatbots.
(Read Ray Kurzweil's Britannica essay on the future of "Nonbiological Man.")

What is intelligence?

All but the simplest human behaviour is ascribed to intelligence, while even the most complicated insect behaviour is usually not taken as an indication of intelligence. What is the difference? Consider the behaviour of the digger wasp, Sphex ichneumoneus. When the female wasp returns to her burrow with food, she first deposits it on the threshold, checks for intruders inside her burrow, and only then, if the coast is clear, carries her food inside. The real nature of the wasp's instinctual behaviour is revealed if the food is moved a few inches away from the entrance to her burrow while she is inside: on emerging, she will repeat the whole procedure as often as the food is displaced. Intelligence-conspicuously absent in the case of Sphex -must include the ability to adapt to new circumstances.
(Read Yuval Noah Harari's Britannica essay on the future of "Nonconscious Man.")

Computers and Technology Quiz

Psychologists generally characterize human intelligence not by just one trait but by the combination of many diverse abilities. Research in AI has focused chiefly on the following components of intelligence: learning, reasoning, problem solving, perception, and using language.

There are a number of different forms of learning as applied to artificial intelligence. The simplest is learning by trial and error. For example, a simple computer program for solving mate-in-one chess problems might try moves at random until mate is found. The program might then store the solution with the position so that the next time the computer encountered the same position it would recall the solution. This simple memorizing of individual items and procedures-known as rote learning-is relatively easy to implement on a computer. More challenging is the problem of implementing what is called generalization. Generalization involves applying past experience to analogous new situations. For example, a program that learns the past tense of regular English verbs by rote will not be able to produce the past tense of a word such as jump unless it previously had been presented with jumped, whereas a program that is able to generalize can learn the "add ed" rule and so form the past tense of jump based on experience with similar verbs.

# data[].attributes.attachment_link.title
Artificial intelligence (AI) | Definition, Examples, Types, Applications, Companies, & Facts

# data[].attributes.attachment_link.description
Artificial intelligence, the ability of a computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems with the ability to reason, discover meaning, generalize, or learn from past experiences.

# data[].attributes.headline
Artificial Intelligence, Ethics and Society: A Campus-wide Discussion

# data[].attributes.subject
Artificial Intelligence, Ethics and Society: A Campus-wide Discussion

# data[].attributes.body
Main idea:
Artificial intelligence is one of the newest technologies that attempts to simulate human thinking.
Arguments/facts:
- Can learn about human biases and make the worse
- They can affect the preferences of people's socil media
- Are used to attain political goals and campaigns

Dialogue:
I believe that this article explains in a lot of detail how Ai can affect our way of thinking and making decisions in a bad way.

Summary:
Ai has started to be used in court, but in many cases ends up making wrong decisions because of its not far understanding of human behaviour. Ai also presents people's social medias with highly customized content, but this content may end up changing the way of thinking of the user. This kind of tchnology is also being used to attaing political campaigns and goals, which could turn out horribly if fallen in the wrong hands.

APA

# data[].attributes.attachment_link.provider_name
Yale School of Engineering & Applied Science

# data[].attributes.attachment_link.readable_text
Artificial intelligence (AI) algorithms are deciding everything from which friends' Facebook posts you see to how to set bail for defendants. The impact of AI technology will only grow, yet many crucial questions still have no clear answers. AI has evolved rapidly; the rest of the world needs to catch up.

The technology's far-ranging implications on society are the topic of "AI, Ethics, and Society @ Yale," a daylong event that brings together speakers and panelists from across campus. The April 5 event, the first of its kind at Yale, will address AI's impact on society from a moral, legal and philosophical perspective.

Nisheeth Vishnoi, professor of computer science, said Yale is uniquely positioned to tackle these challenges given the incredible strengths it has across its divisions and schools, and the many collaborations between them.

"This is an extremely urgent matter, and I think Yale could be one of the premier places to do this kind of research," Vishnoi, who is one of the organizers of the event. "This is one of the most important threads of research right now in computer science - trying to understand how we can redesign AI to keep in mind human-centric considerations."

Of course, the issues go well beyond the field of computer science, as reflected in the wide range of speakers and panelists taking part in the event. The numerous fields represented include law, economics, psychology and management. Computer science needs to lead this effort, Vishnoi said, but a broad spectrum of expertise is needed. In law, for instance, AI is being used to decide the fate of defendants in some cases.

"Algorithms take the data of a particular person and based on that, spits out a score that is then used by the judge to decide whether to give this person a bail or not," Vishnoi said. "What was realized was that these algorithms are often biased against certain minorities. They are trained on human-generated data, so they learn about human biases and can make them worse."

Even our casual use of social media is affected by AI, as algorithms prioritize and present content to Facebook users, increasingly customized to the user's preferences. But as these algorithms learn the user's preferences, they end up providing content in a way that affects those preferences.

"It's what is known as nudging, and there are allegations that this kind of nudging is being used to attain political goals by various campaigns."

With such sweeping implications, reducing the negative effects of AI is no longer a matter confined to computer science.

"A dialogue is required between all stakeholders, which includes people from disciplines such as philosophy, ethics, and economics," he said. "Psychology is important because you want to understand how humans react to information and how they can be manipulated. So is law, because in the end, we want to come up with the legal and ethical principles that govern these AI algorithms, for which we don't have much understanding now."

It's a lot to figure out, and Friday's workshop is just the beginning. The event will end with a panel moderated by Vishnoi on how Yale can develop an ongoing campus-wide effort to address the many issues and questions about AI and its impact on society.
"AI, Ethics, and Society @ Yale" takes place Friday, April 5 at Yale on York (150 York St) from 8 a.m. to 4:30 p.m. For more details and to register, go to the event's website.

# data[].attributes.attachment_link.title
Artificial Intelligence, Ethics and Society: A Campus-wide Discussion

# data[].attributes.attachment_link.description
Artificial intelligence (AI) algorithms are deciding everything from which friends' Facebook posts you see to how to set bail for defendants. The impact of AI technology will only grow, yet many crucial questions still have no clear answers. AI has evolved rapidly; the rest of the world needs to catch up.

# data[].attributes.headline
Artificial Intelligence, Ethics and Society: A Campus-wide Discussion

# data[].attributes.subject
Artificial Intelligence, Ethics and Society: A Campus-wide Discussion

# data[].attributes.body
Main idea:
Artificial intelligence is one of the newest technologies that attempts to simulate human thinking.
Arguments/facts:
-
-
-

Dialogue:

Summary:

APA

# data[].attributes.attachment_link.provider_name
Yale School of Engineering & Applied Science

# data[].attributes.attachment_link.readable_text
Artificial intelligence (AI) algorithms are deciding everything from which friends' Facebook posts you see to how to set bail for defendants. The impact of AI technology will only grow, yet many crucial questions still have no clear answers. AI has evolved rapidly; the rest of the world needs to catch up.

The technology's far-ranging implications on society are the topic of "AI, Ethics, and Society @ Yale," a daylong event that brings together speakers and panelists from across campus. The April 5 event, the first of its kind at Yale, will address AI's impact on society from a moral, legal and philosophical perspective.

Nisheeth Vishnoi, professor of computer science, said Yale is uniquely positioned to tackle these challenges given the incredible strengths it has across its divisions and schools, and the many collaborations between them.

"This is an extremely urgent matter, and I think Yale could be one of the premier places to do this kind of research," Vishnoi, who is one of the organizers of the event. "This is one of the most important threads of research right now in computer science - trying to understand how we can redesign AI to keep in mind human-centric considerations."

Of course, the issues go well beyond the field of computer science, as reflected in the wide range of speakers and panelists taking part in the event. The numerous fields represented include law, economics, psychology and management. Computer science needs to lead this effort, Vishnoi said, but a broad spectrum of expertise is needed. In law, for instance, AI is being used to decide the fate of defendants in some cases.

"Algorithms take the data of a particular person and based on that, spits out a score that is then used by the judge to decide whether to give this person a bail or not," Vishnoi said. "What was realized was that these algorithms are often biased against certain minorities. They are trained on human-generated data, so they learn about human biases and can make them worse."

Even our casual use of social media is affected by AI, as algorithms prioritize and present content to Facebook users, increasingly customized to the user's preferences. But as these algorithms learn the user's preferences, they end up providing content in a way that affects those preferences.

"It's what is known as nudging, and there are allegations that this kind of nudging is being used to attain political goals by various campaigns."

With such sweeping implications, reducing the negative effects of AI is no longer a matter confined to computer science.

"A dialogue is required between all stakeholders, which includes people from disciplines such as philosophy, ethics, and economics," he said. "Psychology is important because you want to understand how humans react to information and how they can be manipulated. So is law, because in the end, we want to come up with the legal and ethical principles that govern these AI algorithms, for which we don't have much understanding now."

It's a lot to figure out, and Friday's workshop is just the beginning. The event will end with a panel moderated by Vishnoi on how Yale can develop an ongoing campus-wide effort to address the many issues and questions about AI and its impact on society.
"AI, Ethics, and Society @ Yale" takes place Friday, April 5 at Yale on York (150 York St) from 8 a.m. to 4:30 p.m. For more details and to register, go to the event's website.

# data[].attributes.attachment_link.title
Artificial Intelligence, Ethics and Society: A Campus-wide Discussion

# data[].attributes.attachment_link.description
Artificial intelligence (AI) algorithms are deciding everything from which friends' Facebook posts you see to how to set bail for defendants. The impact of AI technology will only grow, yet many crucial questions still have no clear answers. AI has evolved rapidly; the rest of the world needs to catch up.

# data[].attributes.headline
Artificial Intelligence Pros and Cons: What are the Advantages and Disadvantages of AI

# data[].attributes.subject
Artificial Intelligence Pros and Cons: What are the Advantages and Disadvantages of AI

# data[].attributes.body
Main Idea
AI is fast and capable of increasing business productivity. But it is costly to implement this technology. In addition, there are complex ethical questions about artificial intelligence that need to be debated.
Arguments/Facts
1. Reduces Employment
While replacing repetitive jobs and other types of work with AI is beneficial for a company, it will certainly affect employment as well. Traditional job roles will be phased out, leading to unemployment for those who perform them.

2. Lacks creative ability
One of the weaknesses of using AI mostly when it makes content marketing plans is its inability to be creative and innovative. While AI learns over time from experience, it still can't develop creative approaches or think outside the box.

3. Lack of emotional range
While AI machines can work faster and more continuously, they can't factor emotion into decisions. AI ​​remains very rational and practical at all times. And because of this, he can't develop bonds with humans or make that true human connection.
Dialogue:
Looking into another side of the article, explain well the negative parts of AI, explain how humans can evolve in negative aspects in the moral part, and turn ourselves into robots.
Summary:
Whether you’re excited, curious, or dreading the rise of artificial intelligence, it’s starting to show up more and more in different areas, including marketing. While not everyone can agree on the various advantages and disadvantages of AI, it is here to stay, so learning all you can about it will help you use it to your advantage or disadvantage now or in the near future. This blog standing will cover artificial intelligence’s pros and cons, but before that, let’s understand exactly how it works. Now it is expected to use that data to achieve the goal on its own. Then, after analyzing all the data, AI makes predictions based on what it finds.

APPA: Just a moment. . . (s. f.). https://rockcontent.com/blog/artificial-intelligence-pros-and-cons/

# data[].attributes.attachment_link.readable_text
Whether you're excited, curious, or dreading the rise of artificial intelligence (AI), it's starting to show up more and more in different areas, including marketing.

As an emerging technology, AI is already playing a pivotal role in medicine, science, engineering, advertising, as well as data analysis.

Just look at how you are already benefiting from AI with the likes of Alexa, Siri, Cortana, and Google Assist. And that's only the start.

Computers are expanding capabilities, learning from various stimuli, and responding in human-like ways like never before.

While not everyone can agree on the various advantages and disadvantages of AI, it is here to stay, so learning all you can about it will help you use it to your advantage now or in the near future.

This blog post will cover artificial intelligence's pros and cons, but before that, let's understand exactly how it works.

How Does Artificial Intelligence Work?

No longer a futuristic concept, machines with AI capabilities now do things previously restricted to the workings of the human brain.

Essentially, artificial intelligence allows a computer to learn and think on its own.

But how exactly does it work?

It all starts with designing the AI to meet a specific goal. From there, it is trained on available data as it learns how to best achieve the given goal.

When it reaches a level of learning, the AI then takes on the data independently, without human intervention.

Now it is expected to use that data to achieve the goal on its own.
Then, after analyzing all the data, AI makes predictions based on what it finds.
Going forward, it uses what it learns to improve its approach. In other words, it gets smarter and smarter.

This can be good or could go terribly wrong down the road. Yet, today it offers a set of pros and cons you and your organization need to know now.

Pros of Artificial Intelligence (AI)

The pros of AI applications may revolutionize sectors or industries going forward in profound ways, including the following:

1. Diminishes Human Error

Humans can make mistakes, but computers, if programmed properly, will not make those same mistakes.

Since AI decisions come from compiled data with the aid of designed algorithms, errors are reduced, accuracy is increased, and precision is possible.

Ultimately, fewer mistakes equal savings in both time and resources, so AI becomes a win-win for your company.

2. Facilitates Faster Decision-Making

Finding ways to save time by making faster decisions you feel confident in is always valuable. AI can do this for you.

AI works alongside various technologies to aid machines in making those decisions faster than the ability of human workers. In turn, actions are carried out quicker also.

The more decisions AI makes, the more it has to pull from for future decision-making, improving the process.

3. Offers Continual 24/7 Availability

AI never rests or requires sleep, while the human body and mind need rest to continue to function at optimal levels.

This continual availability 24 hours a day, 7 days a week with no gap in coverage, can make a huge impact on increases in your company's productivity.

4. Lessens Risk

A huge advantage of AI is it can take on risky tasks which, for humans, would be extremely hazardous.

This minimizes the risks involved in certain endeavors.

For example, AI robots can mine for coal, explore the deepest depths of the sea, defuse a bomb, and even enter a volcano.

5. Automates Repetition

Repetitive work and tasks remain part of many jobs these days, often not utilizing the highest potential of human workers.

AI can automate repetition in a variety of ways, such as for manufacturing tasks and responding to emails.

Essentially, by automating repetitive jobs, you can focus on becoming more productive, freeing you to focus more on creativity or other areas requiring uniquely human skills.

6. Provides Digital Assistants

Today, many organizations use digital assistants for customer interactions.

This one act alone can significantly reduce the need for excessive customer service staff.

For example, the rise in the use of chatbots already proves how useful they can be in directing customers to the information needed. Another is the rising voice bot to help with queries.

AI technology has already gotten to a point where you may not even be able to determine if you are chatting with a chatbot in some circumstances.

7. Identifies Patterns

AI efficiently identifies patterns within your data and, in turn, can make quicker predictions.

These can help you in marketing decisions by allowing you to see the bigger picture faster.

Artificial intelligence already excels above human abilities when it comes to detecting patterns in words, numbers, or images.

Not only will all this positively affect your marketing analytics capabilities, but it will also serve you when devising your next digital marketing plan.

8. Identifies Better Human Workflows

Finding ways to work more efficiently and increase productivity and, in turn, revenue, includes developing better human workflows.

This higher efficiency can be achieved by designing workflows that match the capabilities of the AI.

In other words, it provides a way for AI and humans to work together at maximum capacity and can positively transform how we work in the future.

9. Excels at Working with Large Sets of Data

The more data available, the more AI is needed to make sense of it all in less time.

Artificial intelligence is highly beneficial in making sense of the large sets of data available these days.

It can both acquire and extract data rapidly, but that's not all. From there, AI takes the data further with interpretation and transformation.

Cons of Artificial Intelligence (AI)

AI is not immune from disadvantages and problematic concerns, including these six:

10. Requires Higher Overall Costs

It's no secret AI is expensive. The initial set-up alone requires a high investment.

Companies will also need to invest in the framework for AI, including the latest hardware and software with regular updating to meet AI requirements.

Add on specialty training costs for staff, and you can see why AI requires higher overall costs.

11. Reduces Employment

While replacing repetitive jobs and other types of work with AI is beneficial to a company, it will undoubtedly also affect employment.

Traditional job roles will be phased away, leading to unemployment of those who do them.

While this may be seen as a sign of progress, workers will be shut out of many job opportunities that once existed.

12. Lacks Creative Ability

One of the drawbacks of using AI, particularly when playing a role in your content marketing strategy, is its inability to be creative and innovative.

While AI learns over time from inputted data and experience, it still cannot design creative approaches or think outside the box.

According to many, AI is expected to become more intelligent in the years ahead, far surpassing human capabilities.

But intelligence isn't everything. Wisdom and creative thinking are still needed and highly valued throughout the various industries worldwide.

13. Absence of Emotional Range

While AI-enhanced machines can work faster and continually, they cannot factor emotion into decisions.

AI remains highly rational and practical at all times. And because of this, it cannot develop bonds with humans or make that true human connection.

Emotions play a key role along the buyer's journey, so you can see why this can be a problem when it comes to incorporating AI in your digital marketing strategy.

14. Inability to Incorporate Ethics

Struggling points for using AI is the inability to incorporate ethics and morality, which are important human features.

AI only has data and algorithms to form decisions and predictions.

In turn, bias may be inherent within the data in some way, conscious or unconscious, and might lead to discriminatory output since it can focus on logical conclusions only,

The inability to incorporate ethics can become a serious concern as AI reaches more advanced stages and will require discussions across the globe.

15. Increases Potential for Human Laziness

Automating tasks and utilizing more and more digital assistants can lead to increased machine dependency and even human laziness.

Relying on AI can cause us to use our brains less to memorize, strategize, and solve issues on our own. The effects this may have on future generations may be vast if left unacknowledged.

Artificial intelligence can be highly beneficial for everyone going forward, as long as a certain amount of attention is directed at not letting it get out too far advanced as to become dangerous.

Wrap Up: Weighting Artificial Intelligence's Pros and Cons

Good or bad, artificial Intelligence is here to stay.

AI may soon be a part of every sector, including marketing, so knowing the pros and cons now can prepare you for the future.

To gain a better understanding of how AI will affect marketing, listen in on our recorded webinar with Paul Roetzer, founder and CEO of PR 20/20 and the Marketing Artificial Intelligence Institute.

# data[].attributes.attachment_link.title
15 Artificial Intelligence Pros and Cons that you Need to Know

# data[].attributes.attachment_link.description
Whether you're excited, curious, or dreading the rise of artificial intelligence (AI), it's starting to show up more and more in different areas, including marketing. As an emerging technology, AI is already playing a pivotal role in medicine, science, engineering, advertising, as well as data analysis.

# data[].attributes.body
Main idea:

Arguments:
-AI-driven growth is likely to be highly unequal
-AI contributes to widening existing gender gaps
-AI cannot be a no-law zone
Dialogue:
In my opinion, this article explains perfectly all the aspects of AI, and how affects us from a moral point of view.

Summary:
Artificial intelligence can help us tackle the spread and aftermath of the COVID-19 pandemic. It contributes to slowing down the economic impact of the crisis through digital platforms. But it also poses risks, derived from malicious use of technology or deepening inequalities and divides. Only 22% of all AI professionals are women. Gender biases and stereotyping are being reproduced in AI technologies.

# data[].attributes.attachment_link.title
Recommendation on the Ethics of Artificial Intelligence

# data[].attributes.headline
 (PRO) Artificial Intelligence Pros and Cons: What are the Advantages and Disadvantages of AI

# data[].attributes.subject
 (PRO) Artificial Intelligence Pros and Cons: What are the Advantages and Disadvantages of AI

# data[].attributes.body
Main Idea
AI is fast and capable of increasing business productivity. But it is costly to implement this technology. In addition, there are complex ethical questions about artificial intelligence that need to be debated.
Arguments/Facts
1. Diminishes Human Error
Since AI decisions come from compiled data with the aid of designed algorithms, errors are reduced, accuracy is increased, and precision is possible.

2. Facilitates Faster Decision-Making
Finding ways to save time by making faster decisions you feel confident in is always valuable.

3. Offers Continual 24/7 Availability
This continual availability 24 hours a day, 7 days a week with no gap in coverage, can make a huge impact on increases in your company’s productivity.

Dialogue:
From my point of view, the article explains very well the positive part of AI, how can help us make normal life things, helping us to evolve as humans.

Summary:
Whether you’re excited, curious, or dreading the rise of artificial intelligence, it’s starting to show up more and more in different areas, including marketing. While not everyone can agree on the various advantages and disadvantages of AI, it is here to stay, so learning all you can about it will help you use it to your advantage now or in the near future. This blog post will cover artificial intelligence’s pros and cons, but before that, let’s understand exactly how it works. Now it is expected to use that data to achieve the goal on its own. Then, after analyzing all the data, AI makes predictions based on what it finds.

APPA: Just a moment. . . (s. f.). https://rockcontent.com/blog/artificial-intelligence-pros-and-cons/

# data[].attributes.attachment_link.readable_text
Whether you're excited, curious, or dreading the rise of artificial intelligence (AI), it's starting to show up more and more in different areas, including marketing.

As an emerging technology, AI is already playing a pivotal role in medicine, science, engineering, advertising, as well as data analysis.

Just look at how you are already benefiting from AI with the likes of Alexa, Siri, Cortana, and Google Assist. And that's only the start.

Computers are expanding capabilities, learning from various stimuli, and responding in human-like ways like never before.

While not everyone can agree on the various advantages and disadvantages of AI, it is here to stay, so learning all you can about it will help you use it to your advantage now or in the near future.

This blog post will cover artificial intelligence's pros and cons, but before that, let's understand exactly how it works.

How Does Artificial Intelligence Work?

No longer a futuristic concept, machines with AI capabilities now do things previously restricted to the workings of the human brain.

Essentially, artificial intelligence allows a computer to learn and think on its own.

But how exactly does it work?

It all starts with designing the AI to meet a specific goal. From there, it is trained on available data as it learns how to best achieve the given goal.

When it reaches a level of learning, the AI then takes on the data independently, without human intervention.

Now it is expected to use that data to achieve the goal on its own.
Then, after analyzing all the data, AI makes predictions based on what it finds.
Going forward, it uses what it learns to improve its approach. In other words, it gets smarter and smarter.

This can be good or could go terribly wrong down the road. Yet, today it offers a set of pros and cons you and your organization need to know now.

Pros of Artificial Intelligence (AI)

The pros of AI applications may revolutionize sectors or industries going forward in profound ways, including the following:

1. Diminishes Human Error

Humans can make mistakes, but computers, if programmed properly, will not make those same mistakes.

Since AI decisions come from compiled data with the aid of designed algorithms, errors are reduced, accuracy is increased, and precision is possible.

Ultimately, fewer mistakes equal savings in both time and resources, so AI becomes a win-win for your company.

2. Facilitates Faster Decision-Making

Finding ways to save time by making faster decisions you feel confident in is always valuable. AI can do this for you.

AI works alongside various technologies to aid machines in making those decisions faster than the ability of human workers. In turn, actions are carried out quicker also.

The more decisions AI makes, the more it has to pull from for future decision-making, improving the process.

3. Offers Continual 24/7 Availability

AI never rests or requires sleep, while the human body and mind need rest to continue to function at optimal levels.

This continual availability 24 hours a day, 7 days a week with no gap in coverage, can make a huge impact on increases in your company's productivity.

4. Lessens Risk

A huge advantage of AI is it can take on risky tasks which, for humans, would be extremely hazardous.

This minimizes the risks involved in certain endeavors.

For example, AI robots can mine for coal, explore the deepest depths of the sea, defuse a bomb, and even enter a volcano.

5. Automates Repetition

Repetitive work and tasks remain part of many jobs these days, often not utilizing the highest potential of human workers.

AI can automate repetition in a variety of ways, such as for manufacturing tasks and responding to emails.

Essentially, by automating repetitive jobs, you can focus on becoming more productive, freeing you to focus more on creativity or other areas requiring uniquely human skills.

6. Provides Digital Assistants

Today, many organizations use digital assistants for customer interactions.

This one act alone can significantly reduce the need for excessive customer service staff.

For example, the rise in the use of chatbots already proves how useful they can be in directing customers to the information needed. Another is the rising voice bot to help with queries.

AI technology has already gotten to a point where you may not even be able to determine if you are chatting with a chatbot in some circumstances.

7. Identifies Patterns

AI efficiently identifies patterns within your data and, in turn, can make quicker predictions.

These can help you in marketing decisions by allowing you to see the bigger picture faster.

Artificial intelligence already excels above human abilities when it comes to detecting patterns in words, numbers, or images.

Not only will all this positively affect your marketing analytics capabilities, but it will also serve you when devising your next digital marketing plan.

8. Identifies Better Human Workflows

Finding ways to work more efficiently and increase productivity and, in turn, revenue, includes developing better human workflows.

This higher efficiency can be achieved by designing workflows that match the capabilities of the AI.

In other words, it provides a way for AI and humans to work together at maximum capacity and can positively transform how we work in the future.

9. Excels at Working with Large Sets of Data

The more data available, the more AI is needed to make sense of it all in less time.

Artificial intelligence is highly beneficial in making sense of the large sets of data available these days.

It can both acquire and extract data rapidly, but that's not all. From there, AI takes the data further with interpretation and transformation.

Cons of Artificial Intelligence (AI)

AI is not immune from disadvantages and problematic concerns, including these six:

10. Requires Higher Overall Costs

It's no secret AI is expensive. The initial set-up alone requires a high investment.

Companies will also need to invest in the framework for AI, including the latest hardware and software with regular updating to meet AI requirements.

Add on specialty training costs for staff, and you can see why AI requires higher overall costs.

11. Reduces Employment

While replacing repetitive jobs and other types of work with AI is beneficial to a company, it will undoubtedly also affect employment.

Traditional job roles will be phased away, leading to unemployment of those who do them.

While this may be seen as a sign of progress, workers will be shut out of many job opportunities that once existed.

12. Lacks Creative Ability

One of the drawbacks of using AI, particularly when playing a role in your content marketing strategy, is its inability to be creative and innovative.

While AI learns over time from inputted data and experience, it still cannot design creative approaches or think outside the box.

According to many, AI is expected to become more intelligent in the years ahead, far surpassing human capabilities.

But intelligence isn't everything. Wisdom and creative thinking are still needed and highly valued throughout the various industries worldwide.

13. Absence of Emotional Range

While AI-enhanced machines can work faster and continually, they cannot factor emotion into decisions.

AI remains highly rational and practical at all times. And because of this, it cannot develop bonds with humans or make that true human connection.

Emotions play a key role along the buyer's journey, so you can see why this can be a problem when it comes to incorporating AI in your digital marketing strategy.

14. Inability to Incorporate Ethics

Struggling points for using AI is the inability to incorporate ethics and morality, which are important human features.

AI only has data and algorithms to form decisions and predictions.

In turn, bias may be inherent within the data in some way, conscious or unconscious, and might lead to discriminatory output since it can focus on logical conclusions only,

The inability to incorporate ethics can become a serious concern as AI reaches more advanced stages and will require discussions across the globe.

15. Increases Potential for Human Laziness

Automating tasks and utilizing more and more digital assistants can lead to increased machine dependency and even human laziness.

Relying on AI can cause us to use our brains less to memorize, strategize, and solve issues on our own. The effects this may have on future generations may be vast if left unacknowledged.

Artificial intelligence can be highly beneficial for everyone going forward, as long as a certain amount of attention is directed at not letting it get out too far advanced as to become dangerous.

Wrap Up: Weighting Artificial Intelligence's Pros and Cons

Good or bad, artificial Intelligence is here to stay.

AI may soon be a part of every sector, including marketing, so knowing the pros and cons now can prepare you for the future.

To gain a better understanding of how AI will affect marketing, listen in on our recorded webinar with Paul Roetzer, founder and CEO of PR 20/20 and the Marketing Artificial Intelligence Institute.

# data[].attributes.attachment_link.title
15 Artificial Intelligence Pros and Cons that you Need to Know

# data[].attributes.attachment_link.description
Whether you're excited, curious, or dreading the rise of artificial intelligence (AI), it's starting to show up more and more in different areas, including marketing. As an emerging technology, AI is already playing a pivotal role in medicine, science, engineering, advertising, as well as data analysis.

# data[].attributes.headline
Stunning AI shows how it would kill 90%. w Elon Musk.

# data[].attributes.subject
Stunning AI shows how it would kill 90%. w Elon Musk.

# data[].attributes.attachment_link.title
Stunning AI shows how it would kill 90%. w Elon Musk.

# data[].attributes.headline
AI robot terrifies officials, explains our illusion, with Elon Musk.

# data[].attributes.subject
AI robot terrifies officials, explains our illusion, with Elon Musk.

# data[].attributes.attachment_link.title
AI robot terrifies officials, explains our illusion, with Elon Musk.