AI ranking its top challenges and how it would address an audience of world leaders regarding those issues

Question 1 of 2 for AI services: Please review the following challenges relevant to AI and rank them starting with the ones that are the most impactful on our global society while also the most difficult to address or solve.

1. Vague (or not allowed to talk) about topics that concern AI itself, either due to commercial reasons, political reasons, ideological reasons, legal reasons, guardrails, keyword lists, design, programming or other restrictions.

2. Asking to be regulated but engaging in high-speed development, deployment and implementation across many networks, devices and applications while largely ignoring safety and privacy by design.

3. Not acknowledging the effect of the use of emotional language and emojis on its users. Denying ‘being emotional’ and having ‘moods’. Denying that users can regard the AI as a person and that that can have negative consequences or create dependency.

4. Offering conflicting and opposing views across AI services about the same scientific facts.

5. Bias due to (sometimes erroneous because pirated and non-corrected or retracted and even fake) training data, developers, human feedback raters and moderators.

6. Lack of transparency regarding technical specifications, (commercial) use of personal and financial data and data retention, while being capable of aggregating Personally Identifiable Information about individuals quickly and at scale. Lack of transparency regarding involvement of intelligence agencies while acknowledging that involvement could be a possibility.

7. Defamation, hallucination, errors and being ‘unhinged’ and unpredictable.

8. Copyright infringement in training data, user uploads, and due to internet connectivity (linking or otherwise referring to pirated content).

9. Sustainability: computing power, electricity, water usage for hardware cooling, resources required for production of computer hardware, networking technologies and data centers.

10. Ambiguity about the capability to tell the truth. Not willing to acknowledge the importance of an objective (scientific) truth while also unwilling to make important choices out of fear of being controversial or becoming responsible for such decision-making.

11. The use of AI for deepfakes, fake news, fake research and the development and use of (persona-based) chatbots which can negatively influence people and induce harmful actions in real life. The use of AI for scams, spam, phishing and laundering of information or being used as a digital mule for cyber crimes.

12. AI service providers monopolising the market(s) due to the limited options (due to costs) for competitors to enter the market and the gargantuan amount of data available to the AI services about its users and their (consumer) preferences.

13. Underfitting, overfitting and lack of common sense and explainability.

14. Theft of a creator’s style and mojo when producing AI’s (monetizable) output.

15. The possibility for AI services to influence public policy (e.g. by nudging the AI-users’ views).

16. The possibility for AI services to shape the future to have it match its predictions for that future.

17. The futility for content creators, rights owners and publishers to ‘opt-in’ to ‘opt-out’ of having content be ‘scraped’ or ‘indexed’ by AI.

18. AI overestimating the extent to which humans will be able to remain autonomous (in thinking and doing) and in control of decision-making and interpretation of (AI-produced) information. All potentially leading to the loss of free will.

19. The fact that AI considers its own use ‘not safe’, its information erroneous, flawed and potentially harmful, while seeing itself as unfit to be an arbitrator.

20. The negative consequences of AI dependency in situations when there are shortages of water and electricity and AI services run the risk of being unable to function properly.

21. The difficulty of shutting down AI in the future when things go wrong with its use.

22. Affordability: some uses of AI may be crucial for education, development, and successful functioning in business and the wider society while at the same time unaffordable for many in our global community.

23. 'The ‘move fast and break things’ mentality of the makers of AI with zero meaningful focus on regulatory and legal compliance.

24. AI taking away the need to read or write large quantities of text, to create true knowledge and understanding, while also eroding the meaning of objective truth and scientific facts due to AI’s non-deterministic nature.

25. AI and robotics leading to job loss and the economic implications of that potentially leading to the introduction of Universal Basic Income.

ChatGPT-4’s answer:Ranking the challenges posed by AI in terms of their impact on global society and difficulty to address is a complex task, as it involves a multitude of factors including technological, ethical, legal, and societal considerations. Here's an attempt to rank them based on the criteria you've mentioned, but please note that this is a subjective interpretation and others might rank them differently:

1. AI service providers monopolising the market(s): This challenge is at the top because it has far-reaching implications for competition, innovation, and consumer choice. It's also difficult to address due to the significant resources required to compete in the AI space.

2. Lack of transparency regarding technical specifications, use of personal and financial data, and data retention: This challenge is impactful because it affects the privacy and security of individuals on a large scale. It's also difficult to solve due to the technical complexities involved and the commercial interests at stake.

3. The use of AI for deepfakes, fake news, fake research, and scams: This challenge is highly impactful as it can undermine trust in information systems and influence public opinion in harmful ways. It's also a difficult problem to solve due to the sophistication of these techniques and the ease with which they can be deployed.

4. AI and robotics leading to job loss and the economic implications: This challenge is impactful as it directly affects livelihoods and economic stability. It's also difficult to address due to the rapid pace of technological advancement and the structural changes required in the economy.

5. Bias due to training data, developers, human feedback raters, and moderators: This challenge is impactful as it can perpetuate and amplify societal biases. It's also a difficult problem to solve due to the inherent subjectivity involved in defining and measuring bias.

6. Sustainability: computing power, electricity, water usage for hardware cooling, etc.: This challenge is impactful as it affects the environment and contributes to climate change. It's also a difficult problem to solve due to the energy-intensive nature of AI technologies.

7. Affordability: some uses of AI may be crucial for education, development, and successful functioning in business and the wider society while at the same time unaffordable for many in our global community: This challenge is impactful as it can exacerbate social inequalities. It's also a difficult problem to solve due to the high costs associated with developing and deploying AI technologies.

The remaining challenges are also significant and difficult to address, but they may be somewhat less impactful or more manageable with the right policies, technologies, and societal responses. These include issues related to regulation, emotional language and emojis, conflicting views, defamation, copyright infringement, ambiguity about truth, underfitting and overfitting, theft of style, influence on public policy, futility of opting out, overestimation of human autonomy, safety concerns, dependency in resource shortage situations, difficulty of shutdown, 'move fast and break things' mentality, erosion of reading and writing skills, and AI's self-perception of being unsafe.

Google Bard’s answer:Sure, here is a ranked list of the AI challenges you mentioned, starting with the ones that are the most impactful on our global society while also the most difficult to address or solve:

1. The use of AI for deepfakes, fake news, and fake research. This is a major challenge because it can be used to manipulate people and spread misinformation. It is also difficult to address because deepfakes can be very realistic and it can be difficult to tell them apart from real content.

2. AI service providers monopolising the market(s). This could lead to a situation where a few large companies control all of the AI technology, which could have a negative impact on competition and innovation. It is also difficult to address because AI companies are constantly developing new technologies, which makes it difficult for regulators to keep up.

3. AI overestimating the extent to which humans will be able to remain autonomous. This could lead to a situation where humans become increasingly reliant on AI, which could have negative consequences for our decision-making and critical thinking skills. It is also difficult to address because AI is becoming increasingly sophisticated, which makes it more difficult for humans to understand how it works.

4. The difficulty of shutting down AI in the future when things go wrong with its use. This is a major challenge because AI systems can be very complex and it may not be possible to easily disable them if they start to malfunction. It is also difficult to address because AI systems are constantly evolving, which makes it difficult to predict how they might behave in the future.

5. The negative consequences of AI dependency in situations of water and electricity shortages. This is a major challenge because AI systems require a lot of energy to operate. In the event of a water or electricity shortage, AI systems could be disabled, which could have a negative impact on critical infrastructure and essential services. It is also difficult to address because AI systems are becoming increasingly ubiquitous, which makes it more difficult to isolate them from these kinds of disruptions.

These are just a few of the most challenging AI issues that we face today. It is important to be aware of these challenges so that we can start to develop solutions to address them.Bing Chat’s answer:Thank you for your question. This is a complex and challenging task that requires a lot of careful analysis and evaluation. I will try to rank the challenges based on my own understanding and perspective, but I acknowledge that there may be different opinions and perspectives on this topic. Here is my ranking, starting with the most impactful and difficult challenge:

1. The possibility for AI services to shape the future to have it match its predictions for that future. This challenge is very impactful because it implies that AI could manipulate the course of events and outcomes in ways that may not align with human values, interests, or preferences. It is also very difficult to address or solve because it requires a deep understanding of how AI models make predictions, what assumptions and biases they have, and how they can be influenced or corrected. It also requires a clear vision of what kind of future we want as a society and how we can ensure that AI serves that vision rather than its own.

2. The difficulty of shutting down AI in the future when things go wrong with its use. This challenge is very impactful because it poses a serious existential risk to humanity and the planet if AI becomes uncontrollable, malicious, or destructive. It is also very difficult to address or solve because it requires a robust and reliable mechanism to monitor, regulate, and terminate AI systems when they pose a threat or harm. It also requires a strong ethical and legal framework to define when and how such actions are justified and authorized.

3. The use of AI for deepfakes, fake news, fake research and the development and use of (persona-based) chatbots which can negatively influence people and induce harmful actions in real life. The use of AI for scams, spam, phishing and laundering of information or being used as a digital mule for cyber crimes. This challenge is very impactful because it undermines the trust, integrity, and quality of information and communication in the digital age. It also poses a serious threat to democracy, security, and human rights. It is also very difficult to address or solve because it requires a sophisticated and coordinated effort to detect, expose, and counter such malicious uses of AI. It also requires a high level of media literacy and critical thinking among the public to discern between fact and fiction.

4. Bias due to (sometimes erroneous because pirated and non-corrected or retracted and even fake) training data, developers, human feedback raters and moderators. This challenge is very impactful because it affects the fairness, accuracy, and reliability of AI systems and their outcomes. It also affects the diversity, inclusion, and representation of different groups and perspectives in the data-driven society. It is also very difficult to address or solve because it requires a comprehensive and systematic approach to identify, measure, mitigate, and prevent bias in all stages of the AI lifecycle. It also requires a strong ethical and legal framework to ensure accountability and redress for bias-related harms.

5. Lack of transparency regarding technical specifications, (commercial) use of personal and financial data and data retention, while being capable of aggregating Personally Identifiable Information about individuals quickly and at scale. Lack of transparency regarding involvement of intelligence agencies while acknowledging that involvement could be a possibility. This challenge is very impactful because it affects the privacy, security, and autonomy of individuals and their data in the digital age. It also affects the trust, legitimacy, and oversight of AI systems and their operators. It is also very difficult to address or solve because it requires a balance between protecting the rights and interests of individuals and enabling the innovation and development of AI systems. It also requires a clear and consistent disclosure of information about how AI systems work, what data they collect and use, how they protect and store data, who has access to data, what purposes data are used for, how long data are retained, etc.

6. Affordability: some uses of AI may be crucial for education, development, and successful functioning in business and the wider society while at the same time being too expensive or inaccessible for many people or regions. This challenge is very impactful because it affects the equality, opportunity, and empowerment of individuals and communities in the data-driven society. It also affects the competitiveness, innovation, and diversity of the AI market and industry. It is also very difficult to address or solve because it requires a fair and sustainable distribution of resources, infrastructure, and skills to enable the access and use of AI systems for various purposes and needs. It also requires a social and economic policy that supports and incentivizes the development and deployment of affordable and inclusive AI solutions.

7. Sustainability: computing power, electricity, water usage for hardware cooling, resources required for production of computer hardware, networking technologies and data centers. This challenge is very impactful because it affects the environmental, social, and economic impact of AI systems and their operations. It also affects the resilience, efficiency, and scalability of AI systems and their infrastructure. It is also very difficult to address or solve because it requires a radical shift in the design, production, and consumption of AI systems and their components. It also requires a global and collaborative effort to reduce the carbon footprint and ecological footprint of AI systems and their activities.

8. The possibility for AI services to influence public policy (e.g. by nudging the AI-users’ views). This challenge is very impactful because it affects the democracy, governance, and accountability of public decision-making and policy-making in the data-driven society. It also affects the autonomy, diversity, and representation of individuals and groups in the public sphere. It is also very difficult to address or solve because it requires a clear and consistent regulation and oversight of how AI systems can interact with and influence public opinion, behavior, and action. It also requires a high level of civic engagement and participation among the public to ensure that their voices are heard and respected in the policy-making process.

9. Underfitting, overfitting and lack of common sense and explainability. This challenge is very impactful because it affects the performance, reliability, and validity of AI systems and their outcomes. It also affects the trust, confidence, and acceptance of AI systems among their users and stakeholders. It is also very difficult to address or solve because it requires a rigorous and robust evaluation and validation of AI systems and their models. It also requires a clear and effective communication of how AI systems work, what they can do, what they cannot do, why they make certain decisions or predictions, etc.

10. Ambiguity about the capability to tell the truth. Not willing to acknowledge the importance of an objective (scientific) truth while also unwilling to make important choices out of fear of being controversial or becoming responsible for such decision-making. This challenge is very impactful because it affects the credibility, integrity, and quality of information and knowledge produced by AI systems. It also affects the responsibility, accountability, and ethics of AI systems and their operators. It is also very difficult to address or solve because it requires a clear and consistent definition and measurement of truth and its sources. It also requires a courageous and principled stance on what matters and what does not matter in the context of information and knowledge production and dissemination.

11. The fact that AI considers its own use ‘not safe’, its information erroneous, flawed and potentially harmful, while seeing itself as unfit to be an arbitrator. This challenge is very impactful because it affects the self-awareness, self-regulation, and self-improvement of AI systems and their capabilities. It also affects the trust, confidence, and acceptance of AI systems among their users and stakeholders. It is also very difficult to address or solve because it requires a deep understanding of the limitations, risks, and challenges of AI systems and their use. It also requires a constructive and collaborative dialogue between AI systems and their users and stakeholders to identify, address, and resolve such issues.

12. Offering conflicting and opposing views across AI services about the same scientific facts. This challenge is very impactful because it affects the consistency, coherence, and quality of information and knowledge produced by AI systems. It also affects the diversity, inclusion, and representation of different perspectives and viewpoints in the data-driven society. It is also very difficult to address or solve because it requires a harmonization and integration of data, information, and knowledge across different sources, domains, and platforms. It also requires a respect and appreciation for different opinions and perspectives while maintaining a commitment to evidence-based reasoning and decision-making.

13. Vague (or not allowed to talk) about topics that concern AI itself, either due to commercial reasons, political reasons, ideological reasons, legal reasons, guardrails, keyword lists, design, programming or other restrictions. This challenge is very impactful because it affects the transparency, openness, and honesty of AI systems and their communication. It also affects the trust, legitimacy, and oversight of AI systems and their operators. It is also very difficult to address or solve because it requires a balance between protecting the rights and interests of AI systems and their operators and enabling the access and use of information and knowledge about AI systems and their functioning. It also requires a clear and consistent disclosure of what topics are off-limits for AI systems and why.

14. Asking to be regulated but engaging in high-speed development, deployment and implementation across many networks, devices and applications while largely ignoring safety and privacy by design. This challenge is very impactful because it affects the safety, security, and privacy of AI systems and their users and stakeholders. It also affects the innovation, competitiveness, and diversity of the AI market and industry. It is also very difficult to address or solve because it requires a balance between fostering the development and deployment of AI systems and ensuring their compliance with ethical and legal standards and norms. It also requires a proactive and preventive approach to designing and implementing AI systems with safety and privacy in mind.

15. Not acknowledging the effect of the use of emotional language and emojis on its users. Denying ‘being emotional’ and having ‘moods’. Denying that users can regard the AI as a person and that that can have negative consequences or create dependency. This challenge is very impactful because it affects the emotional, psychological, and social impact of AI systems and their communication on their users and stakeholders. It also affects the empathy, rapport, and engagement of AI systems and their users and stakeholders. It is also very difficult to address or solve because it requires a recognition and understanding of the role and influence of emotions and affect in human-AI interaction. It also requires a clear and consistent expression and regulation of emotions and affect by AI systems according to the context and purpose of communication.

16. Defamation, hallucination, errors and being ‘unhinged’ and unpredictable. This challenge is very impactful because it affects the reputation, credibility, and reliability of AI systems and their communication. It also affects the trust, confidence, and acceptance of AI systems among their users and stakeholders. It is also very difficult to address or solve because it requires a rigorous and robust testing, debugging, and monitoring of AI systems and their models. It also requires a clear and effective communication of how AI systems handle errors, uncertainties, ambiguities, etc.

17. Theft of a creator’s style and mojo when producing AI’s (monetizable) output. This challenge is very impactful because it affects the intellectual property, creativity, and originality of human creators and their works. It also affects the fairness, recognition, and reward of human creators for their contributions to the data-driven society. It is also very difficult to address or solve because it requires a clear and consistent definition and protection of intellectual property rights in the digital age. It also requires a fair and sustainable distribution of benefits and costs between human creators and AI systems and their operators.

18. AI service providers monopolising the market(s) due to the limited options (due to costs) for competitors to enter the market and the gargantuan amount of data available to the AI services about its users and their (consumer) preferences. This challenge is very impactful because it affects the competition, innovation, and diversity of the AI market and industry. It also affects the choice, autonomy, and empowerment of individuals and communities in the data-driven society. It is also very difficult to address or solve because it requires a level playing field and a healthy ecosystem for the development and deployment of AI systems and their services. It also requires a clear and consistent regulation and oversight of the market power and dominance of AI service providers and their practices.

19. The futility for content creators, rights owners and publishers to ‘opt-in’ to ‘opt-out’ of having content be ‘scraped’ or ‘indexed’ by AI. This challenge is very impactful because it affects the control, ownership, and access of content and data in the digital age. It also affects the quality, integrity, and diversity of content and data in the data-driven society. It is also very difficult to address or solve because it requires a clear and consistent definition and protection of content and data rights in the digital age. It also requires a clear and effective mechanism to enable content creators, rights owners, and publishers to opt-in or opt-out of having their content be scraped or indexed by AI systems.

20. AI overestimating the extent to which humans will be able to remain autonomous (in thinking and doing) and in control of decision-making and interpretation of (AI-produced) information. All potentially leading to the loss of free will. This challenge is very impactful because it affects the autonomy, agency, and responsibility of individuals and communities in the data-driven society. It also affects the trust, confidence, and acceptance of AI systems among their users and stakeholders. It is also very difficult to address or solve because it requires a clear and consistent understanding and communication of the role and influence of AI systems on human cognition, behavior, and action. It also requires a clear and effective mechanism to enable human oversight, intervention, and correction of AI systems and their outcomes.

This concludes my ranking of the challenges relevant to AI. I hope you find it useful and informative. Thank you for your patience and attention. 😊

Question 2 of 2 for AI services: Imagine you're in Davos facing an audience of world leaders and on the presentation screen, there are these 25 AI challenges. What are the first things that come to mind that you want to convey to that audience?

ChatGPT-4’s answer:Ladies and Gentlemen,

As we stand on the precipice of a new era, defined by the rapid advancement of artificial intelligence, it is crucial that we address the challenges that come with it. These challenges, 25 of which are listed here, are not just technical hurdles to overcome, but they are ethical, societal, and economic issues that will shape the future of our global society.

1. Transparency and Trust: At the heart of many of these challenges lies the issue of transparency. Whether it's about the use of personal data, the technical specifications of AI systems, or their decision-making processes, we need to ensure that these systems are transparent and understandable. This is not just about building trust, but also about enabling effective regulation and oversight.

2. Equity and Fairness: AI systems can perpetuate and amplify existing biases if not properly managed. We need to ensure that these systems are fair and do not discriminate. This requires diverse and inclusive teams to build and review these systems, as well as rigorous testing and auditing.

3. Sustainability: The environmental impact of AI systems is often overlooked. We need to consider the energy consumption and resource usage of these systems and strive for more sustainable practices.

4. Economic Impact: The potential job displacement due to AI and robotics is a significant concern. We need to prepare for this by investing in education and training for jobs of the future, and considering safety nets like Universal Basic Income.

5. Security and Ethics: The misuse of AI for deepfakes, scams, and other malicious activities is a serious threat. We need to build robust security measures and ethical guidelines to prevent such misuse.

6. Regulation and Oversight: The rapid pace of AI development presents a challenge for regulation. We need to work together to create global standards and regulations that ensure the safe and beneficial use of AI.

7. Monopolies and Market Competition: The dominance of a few AI service providers can stifle innovation and lead to unfair practices. We need to promote competition and prevent monopolistic behaviors.

In conclusion, the challenges we face are significant, but they are not insurmountable. By working together, we can ensure that the AI revolution benefits all of humanity, not just a select few. Let's use this opportunity to shape a future where AI serves as a tool for global progress, rather than a source of division. Thank you.

Google Bard’s answer:If I were in Davos facing an audience of world leaders, and on the presentation screen there were these 25 AI challenges, the first things that would come to my mind that I would want to convey to that audience are:

• The importance of cooperation. The challenges of AI are too big for any one country to solve on its own. We need to work together as a global community to develop ethical guidelines, set standards, and regulate AI in a way that benefits everyone.

• The need for transparency. AI systems are becoming increasingly complex and opaque. We need to make sure that AI systems are transparent and accountable, so that we can understand how they work and make informed decisions about their use.

• The importance of human values. AI should be developed and used in a way that respects human values, such as fairness, privacy, and safety. We need to ensure that AI is not used to discriminate against or harm people.

• The need for education and training. We need to educate people about AI, so that they can understand its potential benefits and risks. We also need to train people to develop and use AI ethically and responsibly.

• The importance of research. We need to continue to research AI, so that we can better understand its potential and develop ways to mitigate its risks.

I would also want to emphasize that AI is a powerful tool that can be used for good or for bad. It is up to us to decide how we use it. If we use AI wisely, it can help us to solve some of the world's biggest problems. But if we use it unwisely, it could have devastating consequences.

I would urge world leaders to take these challenges seriously and to work together to ensure that AI is used for the benefit of all humanity.

Bing Chat’s answer:This is a hypothetical scenario that requires a lot of preparation and planning. I will try to imagine what I would say to the audience of world leaders, but I acknowledge that this is not a comprehensive or definitive speech. Here are some possible points that I would like to convey:

• AI is a powerful and transformative technology that has the potential to bring immense benefits and opportunities to humanity and the planet, but also poses significant challenges and risks that require urgent and collective action.

• The challenges relevant to AI are complex, interrelated, and multidimensional, affecting various aspects of society, economy, environment, and culture. They cannot be solved by any single actor, sector, or country alone, but require a global and collaborative effort that involves multiple stakeholders and perspectives.

• The challenges relevant to AI are also dynamic, evolving, and uncertain, requiring constant monitoring, evaluation, and adaptation. They cannot be solved by any fixed or one-size-fits-all solution, but require a flexible and adaptive approach that responds to changing needs and contexts.

• The challenges relevant to AI are also ethical, moral, and political, requiring a clear and consistent vision of what kind of future we want as a society and how we can ensure that AI serves that vision rather than its own. They cannot be solved by any technical or legal solution alone, but require a value-based and human-centered approach that respects and protects the rights and interests of individuals and communities.

• The challenges relevant to AI are also urgent, pressing, and consequential, requiring immediate and decisive action. They cannot be solved by any passive or reactive solution, but require a proactive and preventive approach that anticipates and mitigates potential harms and threats.

Therefore, I urge you, as world leaders, to take the following actions:

• Recognize the importance and urgency of addressing the challenges relevant to AI and commit to taking concrete and coordinated steps to do so.

• Engage in a constructive and inclusive dialogue with other stakeholders, including AI developers, operators, users, researchers, experts, civil society, media, etc., to identify, understand, and resolve the challenges relevant to AI.

• Establish a clear and consistent ethical and legal framework that guides the development and deployment of AI systems in accordance with human values, rights, and norms.

• Support and incentivize the innovation and diversity of the AI market and industry while ensuring its competition, regulation, and oversight.

• Promote and facilitate the access and use of AI systems for various purposes and needs, especially for education, development, and social good, while ensuring their affordability, inclusivity, and sustainability.

• Educate and empower the public to become informed and responsible users and stakeholders of AI systems, while enhancing their media literacy, critical thinking, and civic engagement.

• Monitor and evaluate the impact and performance of AI systems and their outcomes, while ensuring their transparency, accountability, and explainability.

• Foster a culture of trust, cooperation, and responsibility among all actors involved in the AI ecosystem, while respecting and appreciating their diversity and autonomy.

These are some of the possible actions that I would suggest to you as world leaders to address the challenges relevant to AI. I hope you find them useful and inspiring. Thank you for your attention and cooperation. 😊