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Key characteristics: innovation, agility, adaptability, customer-centricity, inclusivity, transparency, accountability

Principles: data privacy, ethical AI development and deployment, responsible AI use, human oversight, continuous learning and improvement

Strategies: establish a diverse and inclusive team, invest in AI talent development, collaborate with academia and industry experts, engage with stakeholders and customers, develop AI solutions that address societal challenges, prioritize transparency and accountability

Focus: Ethical considerations

Recommendations:

1. Establish an AI ethics committee with diverse representation to review and approve AI projects and ensure ethical considerations are addressed throughout the development and deployment process.

2. Conduct regular and thorough audits to ensure AI systems are unbiased and not perpetuating discrimination.

3. Develop AI solutions that prioritize privacy and data protection, and clearly communicate the intended use and limitations of the technology to customers.

4. Provide clear channels for customers to voice concerns or complaints about AI systems, and ensure there is a human in the loop to address these concerns.

Why: Ensuring ethical considerations are addressed is not only the responsible thing to do, but it also helps build trust and credibility with customers and stakeholders. Additionally, prioritizing ethical considerations can help mitigate potential legal and reputational risks for the company.

Action that best represents our model:
We chose to highlight the importance of establishing an AI ethics committee with diverse representation to ensure ethical considerations are addressed throughout the AI development and deployment process. We believe this is a critical component of successful brand leadership in AI because it demonstrates a commitment to responsible AI use and helps build trust with customers and stakeholders. By prioritizing ethical considerations, companies can ensure their AI systems are not perpetuating discrimination or causing harm, which can ultimately help mitigate potential legal and reputational risks

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“A model for successful brand leadership in AI”

Clear Vision: Have a clear idea of how AI can help the company achieve its goals

Ethics: Develop ethical guidelines for using AI responsibly

Talent Development: Train a talent pool with the skills required to build, maintain, and use AI

Customer Focus: Use AI to personalize experiences for customers and meet their needs

Continuous Improvement: Stay up-to-date with the latest AI trends and technologies

"Recommendations for companies that want to excel in accessibility in brand leadership in AI"

1. Incorporate accessibility from the start of AI product development, using accessible design frameworks and involving individuals with disabilities in the process.

2. Provide alternative options, such as audio or text-based interfaces, to accommodate individuals with different abilities.

3. Ensure compatibility with assistive technologies, such as screen readers and text-to-speech software.

4. Conduct accessibility testing throughout the development process to identify and address potential barriers to accessibility.

5. Provide training and resources to employees, customers, and other stakeholders on how to use AI products and services in an accessible manner.

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1. We believe that a successful brand leadership of AI includes: Accessibility (how easy this AI can be used and what specific areas this AI tool could help people), Innovation, the understanding for their targeted audience, Scalability and adaptability.

2. The model for successful brand leadership in AI includes: machine learning, problem solving, good scalability and adaptability, accessibility

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Successful brand leadership
-Consider of ethical aspects
-accessibility

Model for success
-Protection of users' data and information
-Respect for users's privacy
-Reliability of resources of data being used
-Transparency of using AI
-Legal aspects of utilizing AI

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Josh, Jason, Ashley

Creating Transparency within AI + Imagery

We believe that successful brand management within AI will build trust within the imagery creator community by fostering collaboration.

Recommendations:

Transparency:  builds trust within the brand and builds community and recognition. Fosters partnership and collaboration.

Compensation: AI is viewed as taking work away from artists and this is a way of offering artists a more sustainable way of creating work. Instead of offering visibility as the only form of compensation.

Visibility: Builds trust because creators are recognized for their work.

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Team: Jessie, Joanna, Flora, Lucy, Wendy

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Team: Jessie, Joanna, Flora, Lucy, Wendy

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Our main consideration is AI in medical field. We divide considerations to two aspects: 1.Privacy for customers/users- information accurate or not.

2.Who can be responsible for the answer that the AI model provides?

(physical AI)

We think AI will be successful to use according to several factors:

Ethical

Accessibility

Easy to trust

Interactive

Accuracy

Our recommendation is related with privacy, which are the cybersecurity awareness for information, and it is significant to create some laws to protect information and personal data.

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Area:

An area we are focused on for creating a successful brand leadership in AI is Thought-leadership. Helping the organization and its stakeholders navigate the ambiguous space of adopting and adapting to new tech. Also become knowledge leaders in the space they operate in.

Recommendations:

Accessible terms and conditions to the layperson (transparency)

Motivate and uplift small businesses and communities around the business

Use AI to make products more user friendly and customized

Build brand loyalty

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Ethical Considerations: Our main consideration for brands investing in AI and their brand leadership is focusing on ethical practices. This includes setting clear privacy boundaries and having open communication with their customers. For example, providing resources and platforms for customers to go to if they are concerned with the privacy policy, as well as addressing concerns that customers face while using AI products such as Alexa, Google Home or Siri with constant listening. In addition, allowing individuals to set boundaries on privacy and what information is allowed to be collected and obtained.

Overall, these companies should have a clear vision on how they will adopt AI and put that vision in place through their ethical and privacy actions in respecting customer boundaries and limitations.

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1)    What is successful brand leadership in AI?

Reducing bias when feeding the model

Who is the one providing the data

Algorithms are innately bias or unconditionally biases

General data is collected by patterns which is built off of stereotypes

Data collected can represent the majority collected and those patterns can be innately biased

How can we exchange value with people – not getting value back

AI can run wild

How can we regulate products?

2)    Successful brand with AI

Privacy policies

Product policies

Responsible prompt engineering

Illuminating blind spots in algorithm

Mandated focus groups spanning demographics and cultures to include in creating algorithms

3)    Recommendation

Reduce biases in the model, feed more information

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Team: Yuwei Cui, Izabella LI, Wenhui Li, Lori Cai

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Team: Yuwei Cui, Izabella LI, Wenhui Li, Lori Cai

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1. Empathy: Successful AI brand leaders understand their customers' needs, emotions, and concerns. Focusing on creating products and services that address those needs and enhance the customer experience.

2. Innovation: constantly innovating and looking for new ways to use AI to enhance their products and services.  Investing in research and development to stay ahead of the curve and provide unique solutions to customer problems.

3. Customer experience: Successful AI brand leaders prioritize customer experience above all else. To prioritize the customer experience, AI companies should design user-friendly interfaces, offer personalized recommendations and services, and provide fast and responsive customer support. They can also implement chatbots or virtual assistants to enhance the customer experience.

4. Customization: To provide customized solutions, AI companies can use data analytics to create personalized recommendations and services. offering customizable product and service options to meet individual customer needs and preferences.

Other Points include privacy and data management, coherence, relevance, etc.

e.g. Google uses AI to power its search engine and other products such as Google Assistant and Google Maps. They also prioritize data privacy and offer customizable options for their services.

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The  model we want to personify for brand leadership in AI is to demystify it, and inspire people to use it as a creative tool for productivity or anything that it can affect change with, and not a solution/fix.

This is to inspire people through transparency. This also lends accountability for the organization, that they are responsible for how the AI is used by everyone.
This also ensures privacy because users are aware of how they use the tool and what it does for you.
What AI can do for you and how you can harness it.

By education, this will create accessibility. So that it is more inclusive across age groups, demographics, ability-groups and geographies.

This will empower people to use AI, not scare them.

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Customer-centric:
AI can create significant value for customers, and successful brand leadership in AI requires a strong focus on delivering value to customers. Build a strong connection with users. Create a unique journey for each user.

Understand customer needs

Develop personalized solutions

Make AI user-friendly

Provide transparency and explainability

Empower customers

Foster a culture of innovation

Measure success

AI developments seen nowadays are innovative and remarkable tech-wise, but we believe AI should take into account what the users need, and create something that can change people's lives.

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Our area of brand leadership in AI is: transparency in data and user's privacy.

Our recommendations:
1. actively communicate security measures that are being taken with user's data
2. think innovatively with how you create trust and connection with users
3. creating an environment of psychological safety within the brand
4. create algorithms that help combat biases in order to reduce inequities
5. educate users on AI systems so they can easily understand where/how their data is being used

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Team: Nadir, Jessie, Kirstie and Roshni
Model for successful brand leadership in AI: Diversity, Equity and Inclusion initiative's and embodying it into every aspect that the company does.

1. Workshops for promoting professional development and creating awareness on DE&I
2. Have quarterly revisits on DE&I goals.
3. Have a fixed number of positions for women, under represented  and people of color in leadership positions.
4. Provide onboarding sessions and sounding boards to promote DE&I.
5. Have authentic and transparent conversations on DE&I and share periodically with employees on what the company does to promote it.
6. Creating accessible solutions so that the visually impaired for example, can access the tool. Such as VR in order to merge visual elements into AI.
7. Create a psychologically safe environment for the employees to thrive in.

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No cyborgs, earth-centered interface.
More human AI
Maintain natural elements and ensure environmental sustainability in the creation and use of AI.
Mindful of environmental impacts.
Emphasize benefits to workers, and empower employees to use AI rather than using AI to replace humans. Focus on the benefits and efficiency brought on by AI assistance as opposed to taking over or replacing people and their jobs.
Bottom-up, not replacing employees, but making their jobs and lives easier and more efficient.
Protecting and empowering people's data and privacy.

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We recommend focusing on the accessibility aspect of the brand's AI technology. This could be coupled with commercials that showcase the technology's approachable and personified nature (e.g., grandpa using the technology). This focus on accessibility we believe will be the easiest way to combat society's natural fear of the evolution of AI technology.

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Our specific aspect of successful brand leadership in AI: agility in the lens of ethical considerations

We recommend adding more human elements to the AI’s brand voice. We recommend changing the broadly known perspective of technology overtaking the human experience to a more positive-neutral message of AI being an assisting tool in an individual’s day-to-day life

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Elmo Li, Yuchieh Lung, Michelle Xu, David Liang

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Elmo Li, Yuchieh Lung, Michelle Xu, David Liang

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Successful brand leadership in AI involves having a clear strategy for implementing AI. It also involves identifying areas where AI can add value, integrating AI into existing processes, and communicating the value of AI. We thus think efficiency is the key when it comes to leading business's strategic vision.

Create a model for successful brand leadership in AI: self learning, machine learning, problem solving, ability to create, face perception, Streaming services, E-commerce

In the case of e-commerce, we strongly recommend when facing rapid/crucial competitions, e-commerce businesses can adapt to AI is through AI copywriting. It's data collection and professional analysis in the field of references will be  revolutionizing the way brands create their content. AI can also be used for greater personalization, improved decision-making ability, and gaining a competitive advantage/ Additionally, mid-sized e-commerce businesses are using AI to streamline their checkout process, pre-qualify customers and leads, create better buyer personas, and identify high-value customers, allowing their sales teams to focus on qualified leads.

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Successful Brand leadership
-Consideration of accessibility
-Responsible use
-Equity and inclusion in affordances

Model For successful brand leadership in AI
-Diversified testing
-Afforadibility
-"Opt in" functions
-Transparency (copyrighting)
-Privacy

Our recommendations are for the responsible and ethical use of the technology. Having elements for siting sources should the AI be used to generate academic or works for informing the public.

Our primary focus on the ethical and diversified accessibility of AI technology use.

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Key characteristics of successful brand leadership in AI
- Inclusion: in terms of content and not biased, inclusive for everyone (gender, age, ethinicity, etc.)
- Ethics: be mindful of sensitive topics (distinguish discriminatory comments and contents, political opinions) e.g.: ChatGPT
- Empathy: humanlike interactions, responsive to emotions
- Customer/social impact: provide informative contents to impact people's life and help with decision-making process
- Privacy: respect the private inputs, avoid data leakage, ensure cybersecurity, inform users about privacy policy and use of terms
- Transparency: disclosure source of information to avoid building biased contents

Recommendations
- Partnerships with various organizations such as academic institutions, research labs, NGOs to leverage their expertise and resources
- Distinguish AI from humans, do not promote your AI as a replacement of human resource, but to take it as a guidance/additional help which enriches human's life.

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- Social media: AI helps customize the content for the users.
car industry: AI is used to assist with the safety feature of cars.
Healthcare industry: AI is used to reduce the mistake that human will make.
-  Model:
Characteristics- accountability, privacy, trustworthiness, credibility, responsibility, ethical concerns, sustainability, reliability.
Principles & Strategies- human center, do it all for human needs, doing good by doing right.
- Highlight the ethical considerations. Ethical issues usually tend to be a human base questions that need a lot of evaluations that the AI can not usually deal with.

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We believe that successful brand leadership in AI will only be possible when the brand takes all ethical considerations into account.

Currently AI is trained on datasets that are inherently biased and reflect years of discriminatory practices in our society. We would want the company to talk about how they built their data sets and removed biases.

For Example - AI assuming that a nurse would always be a female.

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Our brand leadership in AI focused on ethics and privacy.
Some of our models for success includes preventing data breaches, misuse of data and strong cybersecurity.
We have two recommendations
1. Make customer privacy No.1. It will build trust and brand value.
2. Develop a framework for ethical use of data and review it often.