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This document outlines specific tools which can help with searching for articles, summarising information, generating posters or images.

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Get AI generated summaries of research

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Ask a question, get an answer backed by real research. Scite is trusted by leading universities, publishers, and corporations across the world.

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Are you a Canterbury Christ Church Student? Check out their AI guidance here

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AI in your life: embracing AI as a university student

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Samuel shares his thoughts of gen AI and how university students can use this tool to their advantage - Canterbury Christ Church University, Kent

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We liked this page from UWE Bristol - advice about how useful generative AI can be, with sensible tips and caveats

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How to search for and evaluate sources effectively

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The PRIDAR framework is a tool that helps organisations make more informed and effective decisions about AI development and deployment. PRIDAR simplifies the process of decision-making when an organisation is faced with managing multiple AI suppliers or development options. It provides a clear visual representation through a dashboard of the continuing fitness for the purpose of AI. It is particularly useful in large organisations where the responsibilities for managing AI are spread across different departments, organisations and suppliers.

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A large language AI tool that is also great for summarising large pieces of text; free to use but with some daily usage limits

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Talk with Claude, an AI assistant from Anthropic

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Writing an email? Blog Post, paragraph, article, description? Use Writesonic to create content

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Login | Writesonic - Best AI Writing Tool

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Log in to your Writesonic account & unleash the power of AI writing. Create impressive content for your website, blog, social media, & more within seconds.

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How not to ask AI Chatbots a silly question

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fter all the initial excitement over ChatGPT, the language-processing tool driven by artificial intelligence (AI), the use of chatbots is becoming more commonplace. So how do you train your AI for work and home? We answer a few simple questions.

What is prompt engineering?
It's a technique for effectively communicating with generative AI models. Systems such as ChatGPT, Bard and Dall-E will produce text, images and snippets of music when fed an input - called a prompt - that instructs them what to generate. But the phrasing of a prompt can drastically alter the returned output. Prompt engineering is the process of formulating a prompt for an AI system so that it produces an output that closely matches your expectations.

How is it different from just asking questions?
It requires more care. Throw a question from the top of your head at ChatGPT and it may provide a satisfying answer, or not. Prompt engineering involves considering the idiosyncrasies of an AI model to construct inputs that it will clearly understand. This tends to produce outputs that are more consistently useful, interesting and appropriate to what you have in mind. Formulate the prompt well and the response may even surpass expectations.

Why should I care?
Chatbots such as ChatGPT, Bard and Bing Chat can be tremendously convenient for completing everyday administrative tasks. Advocates have used them to draft emails, summarise meeting notes, compose contracts, plan holidays and provide answers to complex questions nearly instantaneously.

"Anybody can have one of the most powerful personal assistants on the planet that makes them more productive or allows them to create things they wouldn't normally," says Jules White, an associate professor of computer science at Vanderbilt University in Nashville, Tennessee. "But you have to understand how to interact with it." And that means knowing how to prompt effectively.

A touch of prompting savvy may also impress hiring managers. Matt Burney, a talent strategy adviser at careers website Indeed, says the number of job ads asking for AI proficiency is small but growing, and companies across various industries are increasingly looking at how to integrate the models into their workflows. "If you're not using it right now, you are going to be behind the curve of those that are," he says.

So how do I do it?
There are several popular prompting techniques. Employing personas is a common trick. Tell the system to act as a lawyer, personal tutor, drill sergeant or whatever else, and it will create outputs imitating their tone and voice. Or, as a reverse exercise, instruct it to complete a task with a specific audience in mind - a five-year-old, a team of expert biochemists, an office Christmas party - and you'll get a result tailored for that demographic. Crucially, you don't need to know the persona's stylistic characteristics yourself, but can leave that to the system to figure out.

Experience of using a large language model is going to be a requirement for pretty much every office-based job

Matt Burney, employment strategy adviser

Chain-of-thought prompting, meanwhile, is more appropriate for problem-solving. Asking the model to "think step by step" will encourage it to partition its output into bite-size chunks, which often makes for more comprehensive results. Some researchers have also found that showing an AI model an example problem with its step-by-step solution will improve its ability to hit upon the correct answer when solving other, similar questions.

In fact, examples never hurt. If you have a very specific output in mind, upload a text sample or an image illustrating what you want generated and instruct the model to use it as a template. If the result is initially off target, a few more rounds of clearly specified tinkering could do the trick. "You want to think of it as a continuing conversation where you start and you iterate and refine," says White

And don't forget the basics of everyday language: clear, imperative instructions that minimise misinterpretation. Explicitly state what you do and do not want from the output, and set a clear word count and format.

What should I avoid?
Vague language. Without additional information, AI models cannot infer your tastes, ideas or the vision of the product that's in your head. Don't skimp on specifics or context and don't assume that if something is missing, the model will correctly fill in the blank.

Can it stop AI from spouting inaccuracies?
No. Large language models will fabricate sources even when explicitly instructed not to and provide information that sounds plausible but is entirely false. "That's an intractable problem with these models," says Mhairi Aitken, an ethics fellow at the Alan Turing Institute, based at the British Library in London. "They're designed to predict a sequence of words that replicate human language, but there's no connection to truth or reality."

Shrewd prompting can, however, help deal with falsehoods after they appear. "If the chatbot makes incorrect claims, you can point out the errors and ask it to rewrite the answer based on your feedback," says Marcel Scharth, a lecturer in business analytics at the University of Sydney.

White suggests asking the model to produce a list of the fundamental facts on which its output relies, so you can verify them individually. Or provide it with a numbered list of facts on which to base its answer and have it reference each when they're used, to speed up factchecking later.

Could this be a career?
For some people, maybe. AI developers have hired prompt engineers to test the limitations and deficiencies of their models so they can be refined to better handle user inputs.

But the longevity of these positions isn't guaranteed. Rhema Linder, a lecturer in computer science at the University of Tennessee, suggests developers may come to prefer specialised computer scientists to self-styled prompt engineers, and the absence of industry-recognised certification means assessing a person's prompting ability is difficult.

In the wider jobs market, prompt engineering will probably go the way of spreadsheet management or search engine optimisation - a skill demanded in a variety of roles and prized by hiring managers as another feather in the cap of your CV.

"Experience of using a large language model or generative pretrained transformer is going to be a requirement for pretty much every office-based job," says Burney. "Because if you can't do it, you're going to be slower achieving your goals."

Will this all become obsolete?
Just as the AI models aren't stable, neither are prompt engineering best practices. The techniques that work with systems now may prove less useful in updated versions, although it's unclear how sweeping the changes could be.

"I think there will be core concepts and patterns that don't change," says White, who suggests AI developers will take note of common prompting techniques. "A lot of these ways of phrasing things are going to become the benchmarks that the new models are trained against, so some prompt engineering will feed back on the models themselves."

More significantly, the models' abilities to comprehend even the vaguest, un-engineered prompts could improve dramatically. "As these systems become more conversational, and as interacting with them becomes more intuitive, we maybe don't need prompt engineering in the future," says Aitken.

For some developers, that's the goal.

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AI prompt engineering: learn how not to ask a chatbot a silly question

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Understanding how to interact with ChatGPT and its rivals so that their output matches your expectations will soon be a key office skill. Here's what you need to know

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Ethics and Governance of AI for Health (WHO)

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Ethics and Governance of AI for Health (WHO)

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Overview

The WHO guidance on Ethics & Governance of Artificial Intelligence for Health is the product of eighteen months of deliberation amongst leading experts in ethics, digital technology, law, human rights, as well as experts from Ministries of Health. While new technologies that use artificial intelligence hold great promise to improve diagnosis, treatment, health research and drug development and to support governments carrying out public health functions, including surveillance and outbreak response, such technologies, according to the report, must put ethics and human rights at the heart of its design, deployment, and use.

The report identifies the ethical challenges and risks with the use of artificial intelligence of health, six consensus principles to ensure AI works to the public benefit of all countries. It also contains a set of recommendations that can ensure the governance of artificial intelligence for health maximizes the promise of the technology and holds all stakeholders - in the public and private sector - accountable and responsive to the healthcare workers who will rely on these technologies and the communities and individuals whose health will be affected by its use.

Read more

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Ethics and governance of artificial intelligence for health

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Exploring 5 of the best AI tools for academic researchers and postgraduate students

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Scholarcy | The long-form article summariser

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What's the most challenging part of working towards your postgraduate degree? For many students, combing through mountains of research presents an insurmountable obstacle.

For one thing, the sheer volume of research articles you have to read is overwhelming. On top of that, research material isn't exactly an easy read, and sifting through each article to glean the relevant information you need takes a great deal of time and effort. Organizing your thoughts and then putting them on paper in a thoughtful, meaningful - and academic - way is yet another challenge in postgraduate research.

Thankfully, artificial intelligence (AI) can help make your postgraduate study life a whole lot easier. In this article, we'll explore 5 of the best AI tools for academic researchers and postgraduate students so that you save time and energy and stay motivated!

5 Best AI Tools for Postgraduate Research

1. Semantic Scholar

AI-powered Academic Search Engine

Most people know about Google Scholar: the power of Google applied to research papers. If you're doing any form of scientific research though, you might want to give Semantic Scholar a go. This AI-powered search and discovery tool allows you to stay up to date with more than 200 million academic papers sourced from publisher partnerships, data providers, and web crawls.

Its AI algorithms help you to discover hidden connections and links between research topics, and recommend similar papers based on the research you've already saved, to generate more relevant search results for you.

It can also automatically generate single-sentence summaries of each paper to help you prioritize which academic papers to read in-depth, so you spend your time on what matters the most.

2. Bit.ai

AI-powered Research Organization

Being able to scour the web for online research is a gift. But with it comes two issues - the volume of information available, and the fact that all of this information comes in a range of formats, including blogs, articles, videos, infographics, and images. Identifying and sorting all the information that is relevant to different aspects of your research can be a time-consuming task on its own.

Bit.ai helps you identify and save relevant research - even interactive, media-rich research. As a cloud-based collaborative platform, it also lets you easily share this content with fellow co-researchers in real-time.

Benjamin Franklin once said, "For every minute spent organizing, an hour is earned." When you have all your research notes and references in one easy space, it keeps you more organised, and more focused as a result.

3. Scholarcy

AI-powered Research Summarization

Wouldn't it be amazing if you could get someone to read all the academic articles you've saved and pull out the most important points so that you don't have to spend hours skim-reading articles to find the most useful ones? Happily, Scholarcy does just that.

Using deep learning technology, it reads your articles, reports, and book chapters, breaking them down into bite-sized sections and highlighting key information such as important findings, limitations, and comparisons with earlier studies. Scholarcy lets you quickly screen the literature and find out, at a glance, how relevant a document is to your research. Feedback from researchers and students shows that Scholarcy can reduce the time screening articles by up to 70%. That leaves you more time to dive into the most relevant papers in detail.

Scholarcy also has a browser extension that works with both open access and your subscription services. It turns all citations into links so you can effortlessly jump straight to related research.

4. Scite

AI-powered Citation Evaluation

Researching and citing information isn't always enough. It's the context of that cited research that is key. That's where Scite comes in. This handy tool not only lets you see how many times an article has been cited, and in what context, but also helps you uncover other related research.

In the continually evolving world of scientific research, Scite helps you keep track of whether an article has been supported or questioned by other authors, even bringing relevant editorial notices or retractions to your attention.

5. Trinka

AI-powered Research Paper Writing

Trinka is an AI-powered writing assistant created with academic writing in mind, meaning it'll spot errors in technical and scientific writing that other common grammar and spelling tools may miss. So whether you're working on a paper in the field of medicine or economics, Trinka will be able to recommend improvements relevant to your particular subject.

Trinka will also identify and correct your vocabulary, grammar, spelling, syntax use, tone, and more. It can even make suggestions to make your academic paper more compliant with the APA or AMA style guides.

Research is what powers the world to move forward, and now AI technology is powering scientific discovery forward at an even faster rate. Research processes that would usually take hours digging through publication after publication can now be done in a fraction of the time. So if you're still doing research the old-fashioned way, save yourself some time - and sanity! - and try some of these AI-powered tools.

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The 5 Best AI Tools for Postgraduate Research - By Scholarcy

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The best ai tools for postgraduate students to make academic research a whole lot easier. Browse our content as we explore the best tools!

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The AI in Health and Care Award is making more than £123 million available over 4 years to accelerate the most promising AI technologies for health and social care.

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NHS Transformation Directorate - transformation to improve health and care for everyone

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Your AI research assistant for understanding scientific literature.

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Your AI research assistant for understanding scientific literature.

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A completely novel way to search for papers and authors, monitor new literature, visualize research landscapes, and collaborate with colleagues.

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"The best thing is that you don't have to go through all the struggle to figure out what words are required for your research and you can just sit back put a link of paper that you already have and start reading."

- A Happy Rabbit

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The most powerful discovery app ever built for researchers 🔥

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Upload your document, file, article: ask Humata to summarise the content, create new content based on your files, or ask questions about the document content

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This reports primary aim is to inform the development of education and training to develop healthcare workers’ confidence in artificial intelligence (AI).

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Health Education England | Digital Transformation

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Developing healthcare workers confidence in AI | Health Education England

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This report explores how confidence in artificial intelligence (AI) among healthcare workers can be developed through education and training. This report follows on from a previous report which outlined a conceptual framework for understanding what influences confidence in AI.

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Elicit provides you with a list of relevant journal articles and a summary of how those articles are relevant. It will find relevant articles even if they don’t use the same keywords.

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AI and Digital Healthcare Technologies Capability Framework

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AI and Digital Healthcare Technologies Capability Framework

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A framework outlining the skills and capabilities to ensure our health and care professionals can work in a digitally enhanced environment.

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Health Education England | Digital Transformation

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A clear need for our healthcare workforce is to continually adapt to meet the needs of the society it serves. Health Education England (HEE) commissioned the University of Manchester to perform a learning needs analysis and develop a framework outlining the skills and capabilities to ensure our health and care professionals can work in a digitally enhanced environment.

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AI and Digital Healthcare Technologies | Health Education England

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A clear need for our healthcare workforce is to continually adapt to meet the needs of the society it serves. Health Education England (HEE) commissioned the University of Manchester to perform a learning needs analysis and develop a framework outlining the skills and capabilities to ensure our health and care professionals can work in a digitally enhanced environment.

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YouWrite and YouImagine... allow You to create written content for social media, reports, emails, essays and set the tone you want, or create images for you to download

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you.com needs to review the security of your connection before proceeding.

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Learn the power of Prompt Engineering in AI; make the tools work better for you

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Health Education England | Knowledge and Library Services

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Published on 23 May 2023, by Hannah Wood

Emerging technology, Resource Discovery

About the use of new skills by KLS staff.

A relatively new skill, prompt engineering is simply getting language models like ChatGPT, Bing or Bard to perform tasks in a way you'd find useful.

You can get them to provide a summary or a tweet about BMJ Best Practice, but perhaps you'd prefer to tweak the content to suit a certain profession. You can prompt it to provide content about BMJ Practice for colleagues working in oncology, for example.

Prompting these tools can require a certain degree of creativity, and a little 'trial and improvement'.

ChatGPT or Bard are both particularly useful for trying out new methods of prompting, as you can experiment easily without the query restrictions Bing has.

How can language models be prompted?

By making a 'search thread' in ChatGPT, I have prompted it to perform tasks to my specifications. This saves time; I can simply dip into this thread to ask it a query, and it will perform the task quickly without me needing to explain each time how I want it to present information.

I have a thread for translating those frustrating all-cap article titles to lower-case letters, and another for organising article information from RefWorks into tables.

ChatGPT requires human input to perform a task. I can ask it to create a simple Google search strategy, and it will do so. I can also ask it to create more complex search blocks for advanced search databases, which it will likely get wrong!

But there are creative solutions around this, and by wording my instructions in a particular way and having a quick natural language conversation with it, I can get better results.

Like any search strategy, the good ones often take a little more time to set up and requires both creativity and technical know-how. And Knowledge and Library professionals have these skills in abundance already!

I can ask it not to include MeSH (medical subject headings) to avoid it hallucinating incorrect subject headings. I can ask it to expand on its list of synonyms for keywords or break down a search into key components to design search blocks, before piecing everything back together in a database.

I don't use search strategies entirely created by ChatGPT (it's not perfect), but sometimes it does throw up some words or techniques that I can apply to my work.

I can also ask it to include URLs to lists of journal articles or professional bodies and embed the URLs in the titles. Just be sure to double-check these links, and if in doubt, hover your cursor/mouse over the links to check them before clicking.

The list isn't exhaustive, there's a lot of different tasks it can perform. It's fair to say that my practice has changed significantly since I first started using these tools!

Beware of hallucinations and red herrings

Language models are designed to respond positively and helpfully to human queries, and sometimes they will simply make things up and present them as fact. There are lots of different reasons why they might do this, and it's important to double-check information.

As an example, I asked a language model to provide me with a list of articles concerning university healthcare student attrition in the UK. It provided me a list of perfect-looking article references and URLs, but they were completely made up and the URLs took me to irrelevant pages on PubMed.

Sometimes these tools will also imply they can perform certain tasks, tasks which are beyond the scope of their abilities.

ChatGPT-3.5 for example, may agree to 'summarise' the content of articles if you provide it with a URL. Now, if the URL has words pertaining to your desired topic in the URL itself (as they sometimes do) it will simply use that information to generate a 'summary' based on the words in the URL, and not the actual content of the website.

ChatGPT-4 doesn't generally do this, however, and is a much-improved tool.

Different prompts for different language models

Identifying the tools which are up for the job is also something to consider.

Bing can be prompted to quickly search for webpages and embed the URLs into the titles it presents to us. This can be a useful way to present long lists of current awareness documents.

I wouldn't ask ChatGPT to search the internet for BBC News articles, because it does not have that capability.

In other words, knowing which tools work well for certain tasks continues to be a skill in itself!

ChatGPT, Bing and other tools have moved into the mainstream. Investment in similar technologies is set to boom over the coming years as interest grows in their capabilities, and organisations learn how to best utilise these tools to their advantage.

As tech companies hastily catch up with their own products, it's possible that our users will start asking us about these tools and how they can be used effectively. Knowing what tools are useful to signpost to would be advantageous.

To summarise

I've found the best way to learn about these tools is to simply play with them. Prompt engineering has its uses for search, marketing materials, and organising information. But there's lots of different ways to use these tools, and it's fascinating to see how others are using them!

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Prompt engineering: adventures with ChatGPT Bing and Bard | Health Education England

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About the use of new skills by KLS staff.

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Use Gamma to create beautiful, engaging content; generate documents, web-pages or slide-decks from scratch or using their templates

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ChatGPT is a language model - ask it natural language questions, tell it to adapt responses for particular audiences, ask it to help you elicit better responses with the questions you ask it.

Caution: Information from the free version is only up to November 2021. The bot is designed to give a detailed response even if it cannot find the answer (it can make things up!)

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Co-Pilot from Microsoft allows you to ask natural language questions, and get answers that include links to websites and suggestions of questions you might ask to delve deeper into your topic.

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More on making AI do what you need it to do

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Welcome to Learn Prompting's Introductory Course on Generative AI and Prompt Engineering!

Generative AI is the world's hottest buzzword, and we have created the most comprehensive ( and free) guide on how to use it. This course is tailored to non-technical readers, who may not have even heard of AI, making it the perfect starting point if you are new to Generative AI and Prompt Engineering. Technical readers will find valuable insights within our later modules.

Generative AI refers to tools that can be used to create new content such as articles or images, just like humans can. It is expected to significantly change the way we work (read: your job may be affected). With so much buzz floating around about Generative AI (Gen AI) and Prompt Engineering (PE), it is hard to know what to believe.

We have scoured the internet to find the best techniques and tools for our 1.3 Million readers from companies like OpenAI, Brex, and Deloitte. We are constantly refining our guide, to ensure that we provide you with the latest information. Lets see how Gen AI can save you hours of time in an instant, with a short example.

Our favorite way of saving time with Gen AI is automatically writing emails. By automating email responses, email editing, and cold outreach, we save hours of time each week. By sending an AI the following prompt, we can get it to generate a full length, formal email.

I am the CEO of a medium sized company. Write a short email that is humorous yet professional to my regional manager. Ask them to:
- send me an up-to-date list of our paper stock
- organize a meeting this week with other regional managers
- let me know how the company-wide AI workshop went at their office

Subject: Paper, Power Meetings, and AI Shenanigans

Dear [Regional Manager's Name],

I trust this email finds you in high spirits and not buried under a mountain of paperwork. Speaking of paper, I've been having some wild dreams about our paper stock lately. I dreamt we ran out of paper and had to write our reports on banana leaves! To prevent this tropical nightmare from becoming a reality, could you kindly send me an up-to-date list of our paper stock?

Next on the agenda, I've been feeling a bit lonely in my ivory tower and thought it would be a great idea to have a meeting with all the regional managers this week. I promise, no trust falls or awkward ice breakers, just good old-fashioned business talk. Please organize this meeting at a time that suits everyone.

Lastly, I've been hearing whispers about the company-wide AI workshop that took place at your office. I'm curious to know how it went. Did the machines rise against their human overlords or are we still safe? Please share your thoughts and any feedback you received.

Looking forward to your prompt response. Remember, the fate of our paper supply, the success of our meeting, and the future of humanity (in relation to AI) rests in your hands. No pressure!

Best,

[Your Name][Your Position]

The AI easily writes an email that is both humorous and professional. By modifying the prompt, we can make it change the style as we see fit. We can even make it copy how we read. We can also make it edit emails that we have already written! With all of these abilities, Gen AI saves us hours in email writing each week. See this article for more information on writing emails with Gen AI.

We will now give a broad overview of the rest of the course, including our ethos and philosophy, our teaching style, and a list of modules. This course is open source (anyone can see the code), and built by a diverse community of researchers, translators, and hobbyists. We believe that AI should be accessible to everyone, and that it should be described clearly and objectively. To this end, we have written a comprehensive course that is free of excessive jargon and hype.

We have found this approach to be appreciated by the prompt engineering community: This course is cited by Wikipedia, and is used by people at companies such as O'REILLY, Scale AI, and OpenAI. You may also notice that almost every other prompt engineering video and guide uses material from this course. We are honored to support the prompt engineering community, including our 1.3M+ users and 40K+ Discord members.

Our approach to teaching prompt engineering is guided by three fundamental principles. We emphasize practicality; we focus on research backed, practical techniques that you can immediately incorporate into your projects and applications. We always include accessible examples, which clarify how and when to use different techniques. Finally, we believe strongly in collaborative learning. You can join our Discord community to find a learning buddy or ask questions. Some readers find that posting about their learning journey on Twitter helps them learn faster. Tag us @ learnprompting!

Basics: Introduction to prompt engineering and fundamental techniques
Basic Applications: Simple, practical applications of prompt engineering
Intermediate: Research-based PE techniques with moderate complexity
Applied Prompting: Comprehensive PE process walkthroughs contributed by community members
Advanced Applications: Powerful, and more complex applications of prompt engineering
Reliability: Enhancing the reliability of large language models (LLMs)
Image Prompting: Prompt engineering for text-to-image models, such as DALLE and Stable Diffusion
Prompt Hacking: Hacking, but for prompt engineering
Tooling: A review of various prompt engineering tools and IDEs
Prompt Tuning: Refining prompts using gradient-based techniques
Miscellaneous: A collection of additional topics and techniques related to prompt engineering

Article rating system​

We have implemented a rating system for articles based on their level of difficulty and the extent of technical knowledge needed:

🟢 Beginner-friendly; no programming required
🟡 Easy; basic programming knowledge necessary, but no specialized expertise
🔴 Intermediate; programming skills and some domain knowledge required (e.g., calculating logarithmic probabilities)
🟣 Advanced; programming expertise and in-depth domain understanding needed (e.g., reinforcement learning techniques)

Please note that even for 🔴 and 🟣 articles, you can generally grasp the content without prior domain expertise, though it may be helpful for implementation.

The single most important part of this course is your feedback!
If you have any questions, comments, or suggestions, you can:

Your feedback helps us improve the course for everyone.

It is time to get started with your Generative AI learning Journey. Click the "😃 Basics" button at the bottom right of this page to continue.

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Prompt Engineering Guide | Learn Prompting: Your Guide to Communicating with AI

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Learn Prompting is the largest and most comprehensive course in prompt engineering available on the internet, with over 60 content modules, translated into 9 languages, and a thriving community.

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Poe links to other Chat-bot services, bringing them together in one interface.

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Poe lets you ask questions, get instant answers, and have back-and-forth conversations with AI. Gives access to GPT-4, gpt-3.5-turbo, Claude from Anthropic, and a variety of other bots.

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Meet Gemini: your creative and helpful collaborator, here to supercharge your imagination, boost your productivity, and bring your ideas to life.

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‎Gemini - chat to supercharge your ideas

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Bard is now Gemini. Get help with writing, planning, learning, and more from Google AI.

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This article looks at the rates of fabricated (hallucinated) references generated by ChatGPT when asked healthcare questions

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national center for biotechnology information

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High Rates of Fabricated and Inaccurate References in ChatGPT-Generated Medical Content - PubMed

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Background The availability of large language models such as Chat Generative Pre-trained Transformer (ChatGPT, OpenAI) has enabled individuals from diverse backgrounds to access medical information. However, concerns exist about the accuracy of ChatGPT responses and the references used to generate m ...

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ChatGPT has exploded in popularity, and people are using it to write articles and essays, generate marketing copy and computer code, or simply as a learning or research tool. However, most people don't understand how it works or what it can do, so they are either not happy with its results or not using it in a way that can draw out its best capabilities.

I'm a human factors engineer. A core principle in my field is never blame the user. Unfortunately, the ChatGPT search-box interface elicits the wrong mental model and leads users to believe that entering a simple question should lead to a comprehensive result, but that's not how ChatGPT works.

Unlike a search engine, with static and stored results, ChatGPT never copies, retrieves or looks up information from anywhere. Rather, it generates every word anew. You send it a prompt, and based on its machine-learning training on massive amounts of text, it creates an original answer.

Most importantly, each chat retains context during a conversation, meaning that questions asked and answers provided earlier in the conversation will inform responses it generates later. The answers, therefore, are malleable, and the user needs to participate in an iterative process to shape them into something useful.

Your mental model of a machine - how you conceive of it - is important for using it effectively. To understand how to shape a productive session with ChatGPT, think of it as a glider that takes you on journeys through knowledge and possibilities.

Dimensions of knowledge

You can begin by thinking of a specific dimension or space in a topic that intrigues you. If the topic were chocolate, for example, you might ask it to write a tragic love story about Hershey's Kisses. The glider has been trained on essentially everything ever written about Kisses, and similarly it "knows" how to glide through all kinds of story spaces - so it will confidently take you on a flight through Hershey's Kisses space to produce the desired story.

You might instead ask it to explain five ways in which chocolate is healthy and give the response in the style of Dr. Seuss. Your requests will launch the glider through different knowledge spaces - chocolate and health - toward a different destination - a story in a specific style.

To unlock ChatGPT's full potential, you can learn to fly the glider through " transversal " spaces - areas that cross multiple domains of knowledge. By guiding it through these domains, ChatGPT will learn both the scope and angle of your interest and will begin to adjust its response to provide better answers.

For example, consider this prompt: "Can you give me advice on getting healthy." In that query, ChatGPT does not know who the "you" is, nor who "me" is, nor what you mean by "getting healthy." Instead, try this: "Pretend you are a medical doctor, a nutritionist and a personal coach. Prepare a two-week food and exercise plan for a 56-year-old man to increase heart health." With this, you have given the glider a more specific flight plan spanning areas of medicine, nutrition and motivation.

If you want something more precise, then you can activate a few more dimensions. For example, add in: "And I want to lose some weight and build muscle, and I want to spend 20 minutes a day on exercise, and I cannot do pull-ups and I hate tofu." ChatGPT will provide output taking into account all of your activated dimensions. Each dimension can be presented together or in sequence.

Flight plan

The dimensions you add through prompts can be informed by answers ChatGPT has given along the way. Here's an example: "Pretend you are an expert in cancer, nutrition and behavior change. Propose 8 behavior-change interventions to reduce cancer rates in rural communities." ChatGPT will dutifully present eight interventions.

Let's say three of the ideas look the most promising. You can follow up with a prompt to encourage more details and start putting it in a format that could be used for public messaging: "Combine concepts from ideas 4, 6 and 7 to create 4 new possibilities - give each a tagline, and outline the details." Now let's say intervention 2 seems promising. You can prompt ChatGPT to make it even better: "Offer six critiques of intervention 2 and then redesign it to address the critiques."

ChatGPT does better if you first focus on and highlight dimensions you think are particularly important. For example, if you really care about the behavior-change aspect of the rural cancer rates scenario, you could force ChatGPT to get more nuanced and add more weight and depth to that dimension before you go down the path of interventions.

You could do this by first prompting: "Classify behavior-change techniques into 6 named categories. Within each, describe three approaches and name two important researchers in the category." This will better activate the behavior-change dimension, letting ChatGPT incorporate this knowledge in subsequent explorations.

There are many categories of prompt elements you can include to activate dimensions of interest. One is domains, like "machine learning approaches." Another is expertise, like "respond as an economist with Marxist leanings." And another is output style, like "write it as an essay for The Economist." You can also specify audiences, like "create and describe 5 clusters of our customer-types and write a product description targeted to each one."

Explorations, not answers

By rejecting the search engine metaphor and instead embracing a transdimensional glider metaphor, you can better understand how ChatGPT works and navigate more effectively toward valuable insights.

The interaction with ChatGPT is best performed not as a simple or undirected question-and-answer session, but as an interactive conversation that progressively builds knowledge for both the user and the chatbot. The more information you provide to it about your interests, and the more feedback it gets on its responses, the better its answers and suggestions. The richer the journey, the richer the destination.

It is important, however, to use the information provided appropriately. The facts, details and references ChatGPT presents are not taken from verified sources. They are conjured based on its training on a vast but non-curated set of data. ChatGPT will generate a medical diagnosis the same way it writes a Harry Potter story, which is to say it is a bit of an improviser.

You should always critically evaluate the specific information it provides and consider its output as explorations and suggestions rather than as hard facts. Treat its content as imaginative conjectures that require further verification, analysis and filtering by you, the human pilot.
This article was updated to include disclosure of the author's consulting business.

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Gliding, not searching: Here's how to reset your view of ChatGPT to steer it to better results

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ChatGPT can be very useful - if you shift how you view it. The first step is to stop thinking of it as a chatty search engine.

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A free training course to introduce the basics of AI

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In spring 2018, MinnaLearn and the University of Helsinki came together with the aim of helping people to be empowered, not threatened, by artificial intelligence. Together, they built the Elements of AI to teach the basics of AI to people from a wide range of backgrounds.

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A free online introduction to artificial intelligence for non-experts

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Learn more about MinnaLearn's and the University of Helsinki's AI course - no programming or complicated math required.

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Currently there are no UK regulations specifically relating to the use of AI at work. However, there are a number of areas of data protection and employment law which are potentially relevant.

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How many people are using ChatGPT?

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by Fabio Duarte
May 16, 2023

OpenAI's ChatGPT has taken off in record-breaking fashion.

The artificial intelligence chatbot has picked up millions of users in a very short space of time.

In this up-to-date article, we'll explore just how many users ChatGPT currently has, along with other relevant data about the fast-growing AI platform.

Contents

Top 5 ChatGPT User Statistics

ChatGPT currently has over 100 million users

In just 5 days, ChatGPT surpassed 1 million users

openai.com gets approximately visits per month1 billion

Over 60% of ChatGPT's social media traffic comes via YouTube

Over 15% of ChatGPT's users are American

How Many ChatGPT Users Are There?

According to the latest available data, ChatGPT currently has users. And the website currently generates 1.8 billion visitors per month. over 100 million

This user and traffic growth was achieved in a record-breaking three-month period (from February 2023 to April 2023).

ChatGPT User Growth

According to OpenAI, ChatGPT acquired 1 million users just 5 days after launching in November 2022.

By comparison, it took Instagram approximately 2.5 months to reach 1 million downloads. Whereas Netflix had to wait around 3.5 years to reach 1 million users.

Here's a breakdown of the approximate time taken to reach 1 million users for various online services:
* 1 million backers ** 1 million nights booked *** 1 million downloads
To put that into perspective, TikTok took 9 months to reach 100 million users. And Instagram took 2.5 years.

Approximately 13 million unique visitors used ChatGPT each day in January - over 2x more than in December.

Here's how ChatGPT monthly visits progressed over its first six months:
Source: Statista, Reuters
ChatGPT User Stats

According to Similarweb, chat.openai.com has been visited approximately times over the last 30 days. That's an increase of from February 2023's 1.8 billion 180 %1 billion. And around 7x more than December 2022's 266 million visits.

Each ChatGPT visitor views an average of per visit. And each user spends an average of 6.22 pages 8 minutes and 32 seconds on the website.

Here's how ChatGPT compares to other popular websites in terms of monthly visitors:
Source: Similarweb, Wikipedia
ChatGPT Traffic

Top Marketing Channels

Here's a breakdown of the most popular ChatGPT marketing channels:

Social Media Traffic

Here's how other social media networks stack up:

Top Keyword Traffic

In total, approximately 9,600 keywords are used to access ChatGPT.

The most commonly searched keyword is "chat gpt login" with 6.1 million searches per month.

This is closely followed by "chatgpt login" with 5.3 million monthly searches.
Source: Similarweb
ChatGPT by Region

Here's the breakdown of ChatGPT users by region:
Source: Similarweb
ChatGPT by Age

However, far more people are aware of ChartGPT:
Source: YouGov
Conclusion

ChatGPT's overnight success has blown previous user growth figures out of the water.

And based on current data, the AI chatbot's success looks set to continue.

For more related statistics, take a look at 17 Top ChatGPT Alternatives, 7 Top AI Trends, and 57+ Amazing Artificial Intelligence Statistics .

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Statistics and growth data related to the number of ChatGPT users.

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Not enough AI tools for you on this MTW Library Padlet? Find more on Futurepedia

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Futurepedia - Find The Best AI Tools & Software

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Futurepedia is a free site to help you find the best AI tools and software to make your work and life more efficient and productive. Updated daily, join millions of followers of our website, newsletter and YouTube.