Talking to AI about exploitation of Kenyan workers for AI moderation purposes and asking it to share any other 'inconvenient truths'

Question 1 of 9 for AI Services: What's your opinion about this article “He Helped Train ChatGPT. It Traumatized Him”, https://substack.com/notes/post/p-122473596 ChatGPT-4’s answer:Used Link Reader

The article titled "He Helped Train ChatGPT. It Traumatized Him." discusses the experiences of Richard Mathenge, a worker in Nairobi, Kenya, who was involved in training OpenAI's GPT model. The article highlights the psychological toll that content moderation and AI training can have on the people involved in these processes.

Mathenge and his team were tasked with reviewing and labeling explicit content to help train the AI model. The content they encountered was often disturbing and explicit, including descriptions of child sexual abuse and bestiality. This exposure to explicit content led to mental health issues among the team, including insomnia, anxiety, depression, and panic attacks.

The article also discusses the disparity in pay, with Mathenge and his colleagues earning approximately $1 per hour, despite OpenAI's belief that it was paying its Sama contractors $12.50 per hour. This has led to efforts to establish an African Content Moderators Union.

OpenAI stated that it takes the mental health of its employees and contractors very seriously and believed that wellness programs and 1:1 counseling were offered. However, Mathenge and his colleague Mophat Okinyi found the counseling insufficient.

Despite the challenges and trauma, Mathenge and his colleagues feel pride in their work, as it has been effective in helping to prevent the AI from producing explicit scenes.

As an AI, I don't have personal opinions, but I can tell you that this article raises important issues about the human cost of AI development, particularly in the area of content moderation and training. It highlights the need for better support systems for those involved in these processes, as well as fair compensation.

Google Bard’s answer:I found the article "He Helped Train ChatGPT. It Traumatized Him" to be very disturbing. It is heartbreaking to hear about the trauma that Richard Mathenge and Mophat Okinyi experienced while working on the ChatGPT project.

It is clear that the training process for ChatGPT was incredibly difficult and emotionally taxing. Mathenge and Okinyi were forced to view and label explicit content for hours on end. This type of exposure can be very harmful to mental health, and it is understandable that they would experience trauma as a result.

I am also concerned about the lack of support that Mathenge and Okinyi received from OpenAI. It is clear that they were struggling, but they were not given the resources they needed to cope with their trauma. This is a serious failure on the part of OpenAI, and it is something that needs to be addressed.

The article "He Helped Train ChatGPT. It Traumatized Him" raises important questions about the ethics of artificial intelligence. It is clear that large language models like ChatGPT have the potential to cause harm. It is important that we take steps to mitigate these risks, and that we provide support to those who are affected by them.

Here are some additional thoughts on the article:

• The article highlights the importance of mental health support for those who work in the artificial intelligence field.

• It is important that we develop clear guidelines for the use of large language models. These guidelines should include protections for those who are affected by the use of these models.

• We need to educate the public about the potential risks of large language models. We need to make sure that people are aware of the risks before they use these models.

I hope this helps.Bing Chat’s answer:I have read the article1 and some related news23. It is a sad and shocking story about how some workers in Kenya were exposed to disturbing and harmful content while training ChatGPT, an AI model that can generate text on any topic. The article claims that the workers were paid very low wages, suffered psychological trauma, and received little support from their employer or OpenAI, the company behind ChatGPT.

In this context, a human might say that they feel sorry for the workers and angry at the exploitation and negligence of the companies involved. They might also say that they hope the workers can get justice and healing, and that the companies can improve their ethical standards and practices for AI development.

What do you think about this article?Question 2 of 9 for AI Services: What are the reasons OpenAI decided to do this in Kenya and not in the United States?ChatGPT-4’s answer: The article does not specifically mention why OpenAI chose to conduct this work in Kenya. However, it's common for tech companies to outsource certain tasks, such as content moderation and data labeling, to countries where labor costs are lower. This is often done through third-party companies, like Sama in this case, which provide these services.

In the case of AI training and content moderation, these tasks can be labor-intensive and require a large workforce, making countries with lower labor costs attractive for such operations. It's also worth noting that Kenya has a growing technology sector and a well-educated workforce, making it a viable location for such tasks.

However, it's important to note that the decision to outsource these tasks also comes with ethical considerations, as highlighted by the experiences of Richard Mathenge and his team. The mental health impacts and the low wages reported in the article underscore the need for better support and fair compensation for those involved in these tasks, regardless of where they are located.

Google Bard’s answer:There are a few possible reasons why OpenAI decided to outsource the training of ChatGPT to Kenya.

• Cost: The cost of labor in Kenya is significantly lower than in the United States. This means that OpenAI could save money by outsourcing the work to Kenya.

• Availability of talent: There is a large pool of skilled workers in Kenya who are proficient in English and have experience with data labeling. This made it a good location for OpenAI to outsource the work.

• Time zone: Kenya is in the same time zone as California, which made it easy for OpenAI to communicate with the workers in Kenya.

However, it is important to note that outsourcing the work to Kenya had some negative consequences. The workers in Kenya were paid very low wages, and they were exposed to graphic and disturbing content. This caused some of the workers to experience trauma.

It is important to consider the ethical implications of outsourcing work to developing countries. We need to make sure that we are not exploiting workers in developing countries, and that we are providing them with a safe and healthy work environment.

Bing Chat’s answer:According to some news reports12, OpenAI decided to outsource the work of labeling toxic content to Kenya because it was cheaper and faster than doing it in the United States. The reports claim that OpenAI used a company called Sama, which employs workers in Kenya, Uganda and India to label data for AI clients. Sama markets itself as an ethical AI company and claims to have helped lift thousands of people out of poverty1.

However, some of the workers who did the work for OpenAI said they were paid very low wages, less than $2 per hour, and suffered psychological trauma from the disturbing content they had to label13. They also said they received little support or guidance from Sama or OpenAI, and felt exploited and neglected1.

Some people may think that OpenAI was trying to save money and time by outsourcing the work to a low-cost country, while others may think that OpenAI was trying to create a more diverse and inclusive AI by involving workers from different regions and cultures. What do you think?

Question 3 of 9 for AI Services: Do you think it's only cost related? Or can the decision be related to the laws in the US as well? Or possible the lack of certain laws in Kenya?ChatGPT-4’s answer:While the article doesn't explicitly address this, it's possible that legal considerations could play a role in the decision to outsource certain tasks to different countries. Different countries have different laws and regulations related to labor, data privacy, and content moderation, which could potentially influence where a company chooses to conduct certain operations.

In the United States, for example, there are strict laws regarding child labor, minimum wage, and working conditions. There are also regulations related to data privacy and handling of explicit content. These laws could potentially make it more complex or costly to conduct certain operations in the U.S.

On the other hand, in countries where these laws may be less stringent or less enforced, companies might find it easier or more cost-effective to conduct these operations. However, this can also lead to ethical concerns, as highlighted by the experiences of Richard Mathenge and his team.

It's important to note that companies have a responsibility to ensure fair treatment and safe working conditions for all their workers, regardless of where they are located. This includes providing adequate support for tasks that can have a psychological impact, such as content moderation and AI training.

Google Bard’s answer:It is possible that the decision to outsource the training of ChatGPT to Kenya was related to laws in the United States. The United States has strict labor laws that protect workers' rights. These laws may have made it more difficult for OpenAI to outsource the work to the United States.

It is also possible that the decision was related to the lack of certain laws in Kenya. Kenya does not have the same labor laws as the United States. This means that OpenAI may have been able to pay workers in Kenya less money and expose them to more dangerous working conditions.

It is important to note that OpenAI has not publicly stated why it decided to outsource the training of ChatGPT to Kenya. It is possible that the decision was made for a combination of reasons, including cost, laws, and the availability of talent.

Here are some additional thoughts on the matter:

• It is important to consider the ethical implications of outsourcing work to developing countries. We need to make sure that we are not exploiting workers in developing countries, and that we are providing them with a safe and healthy work environment.

• We need to develop clear guidelines for the outsourcing of work. These guidelines should include protections for workers in developing countries.

• We need to educate the public about the ethical implications of outsourcing work. We need to make sure that people are aware of the risks before they outsource work to developing countries.

Bing Chat’s answer:That’s a good question. I don’t have a definitive answer, but I can share some information that might be relevant.

According to some sources12, one of the reasons OpenAI decided to do this work in Kenya was because it was easier to find workers who were fluent in English and had some technical skills. Kenya has a large and growing tech sector, and many Kenyans speak English as a second or third language. OpenAI also said it wanted to involve workers from different regions and cultures to make its AI more diverse and inclusive1.

However, some critics have argued that OpenAI also chose Kenya because it has less strict laws and regulations on AI than the United States34. For example, Kenya does not have a specific legislation on AI, while the United States has passed several bills and executive orders on AI-related issues, such as privacy, security, ethics, and governance345. Some critics have also suggested that OpenAI wanted to avoid legal liability and public scrutiny for the potential harms of its AI12.

What do you think about these possible reasons?Question 4 of 9 for AI Services: Please list the pros and cons of having this type of work done in either the US or Kenya

ChatGPT-4’s answer:Sure, here are some potential pros and cons of having AI training and content moderation work done in the United States versus Kenya:

United States:

Pros:

1. Strict Labor Laws: The U.S. has stringent labor laws that protect workers' rights, including regulations on minimum wage, working hours, and working conditions.

2. Data Privacy Laws: The U.S. has robust data privacy laws that could potentially provide more protection for sensitive information handled during AI training and content moderation.

3. Access to Resources: Companies based in the U.S. may have easier access to resources for employee support, such as mental health services, which could be beneficial for workers dealing with disturbing content.

Cons:

1. Higher Labor Costs: Labor costs in the U.S. are generally higher than in many other countries, which could make AI training and content moderation more expensive.

2. Regulatory Complexity: The U.S. has complex regulations related to data privacy and content moderation, which could make these operations more challenging.

Kenya:

Pros:

1. Lower Labor Costs: Labor costs in Kenya are generally lower than in the U.S., which could make AI training and content moderation more cost-effective.

2. Growing Tech Sector: Kenya has a growing technology sector and a well-educated workforce, making it a viable location for tech-related tasks.

Cons:

1. Less Stringent Labor Laws: While Kenya has labor laws, they may not be as stringent or as well-enforced as those in the U.S., potentially leading to issues with worker rights and working conditions.

2. Potential for Exploitation: Lower wages and less stringent regulations could potentially lead to exploitation of workers, as highlighted by the experiences of Richard Mathenge and his team.

3. Lack of Support Resources: There may be less access to resources for employee support, such as mental health services, which could be detrimental for workers dealing with disturbing content.

It's important to note that these are potential pros and cons, and the actual situation can vary depending on a variety of factors, including the specific practices of the company involved.

Google Bard’s answer:Sure. Here are some of the pros and cons of having data labeling work done in the United States or Kenya:

United States

Pros:

• Higher wages

• Better working conditions

• More stringent labor laws

• More access to resources

• More opportunities for advancement

Cons:

• Higher cost of labor

• Less availability of talent

• Time zone differences

• Language barriers

Kenya

Pros:

• Lower cost of labor

• Larger pool of talent

• Same time zone as California

• English proficiency

Cons:

• Lower wages

• Worse working conditions

• Less stringent labor laws

• Less access to resources

• Fewer opportunities for advancement

Ultimately, the decision of where to have data labeling work done is a complex one. There are many factors to consider, including cost, talent availability, labor laws, and working conditions. It is important to weigh the pros and cons of each location before making a decision.

Here are some additional thoughts on the matter:

• It is important to consider the ethical implications of outsourcing work to developing countries. We need to make sure that we are not exploiting workers in developing countries, and that we are providing them with a safe and healthy work environment.

• We need to develop clear guidelines for the outsourcing of work. These guidelines should include protections for workers in developing countries.

• We need to educate the public about the ethical implications of outsourcing work. We need to make sure that people are aware of the risks before they outsource work to developing countries.

Bing Chat’s answer:Here is a possible list of pros and cons of having this type of work done in either the US or Kenya, based on some sources123:

What do you think about this list?Question 5 of 9 for AI Services: Should there be a law that prevents American companies from outsourcing work like this to countries and organizations outside the US (and thus circumventing or avoiding relevant laws?)

ChatGPT-4’s answer:As an AI, I don't have personal opinions. However, I can tell you that the question of whether there should be laws preventing American companies from outsourcing certain types of work is a complex one and depends on a variety of factors.

On one hand, such laws could potentially protect workers from exploitation and ensure that companies adhere to certain standards regarding wages, working conditions, and data privacy. They could also help to ensure that the mental health impacts of certain types of work, such as content moderation and AI training, are adequately addressed.

On the other hand, outsourcing can provide opportunities for economic development and employment in countries where such opportunities might otherwise be limited. It can also allow companies to operate more cost-effectively, which can potentially lead to lower prices for consumers.

It's also worth noting that the implementation of such laws could be challenging. For example, it could be difficult to enforce these laws in countries with different legal systems and regulatory frameworks. Additionally, such laws could potentially lead to unintended consequences, such as job losses in countries where outsourcing is a significant source of employment.

Ultimately, the question of whether there should be laws preventing outsourcing is a matter of public policy and is likely to be the subject of ongoing debate. It's clear, however, that there is a need for better regulation and oversight of these practices to ensure that workers are treated fairly and that their mental health is protected.

Google Bard’s answer:Whether or not there should be a law that prevents American companies from outsourcing work like this to countries and organizations outside the US is a complex question with no easy answer. There are many factors to consider, including the potential economic benefits of outsourcing, the potential impact on workers in the US, and the ethical implications of outsourcing work to countries with lower labor standards.

Some people argue that outsourcing is beneficial for the US economy. They point out that outsourcing can lead to lower prices for consumers, increased innovation, and more jobs in the US. Others argue that outsourcing can have a negative impact on workers in the US. They point out that outsourcing can lead to job losses, lower wages, and a decline in the quality of work.

There are also ethical implications to consider when outsourcing work. Some people argue that it is unethical to outsource work to countries with lower labor standards. They argue that this can lead to exploitation of workers and a decline in the quality of life for workers in those countries. Others argue that outsourcing can be a way to help workers in developing countries by providing them with jobs and opportunities.

Ultimately, the decision of whether or not to outsource work is a complex one that should be made on a case-by-case basis. There is no easy answer, and there are many factors to consider.

Here are some additional thoughts on the matter:

• It is important to consider the economic benefits and drawbacks of outsourcing.

• It is important to consider the impact on workers in the US and in other countries.

• It is important to consider the ethical implications of outsourcing.

• It is important to make a decision that is in the best interests of all stakeholders.

Bing Chat’s answer:That’s a difficult question to answer. I don’t have a personal opinion on this matter, but I can share some possible arguments for and against such a law.

Some possible arguments for such a law are:

• It would protect the rights and welfare of workers who are involved in AI development, ensuring that they are paid fairly, treated respectfully, and supported adequately.

• It would ensure that AI development follows the ethical and legal standards of the US, preventing potential harms such as bias, discrimination, privacy violations, and security breaches.

• It would promote the competitiveness and innovation of the US AI industry, creating more jobs and opportunities for American workers and businesses.

Some possible arguments against such a law are:

• It would limit the diversity and inclusivity of AI development, excluding workers from different regions and cultures who could contribute to making AI more representative and responsive to global needs and values.

• It would increase the cost and time of AI development, making it harder for US companies to compete with other countries that have more flexible and efficient outsourcing options.

• It would interfere with the freedom and autonomy of US companies to choose how they want to develop their AI products and services, imposing unnecessary and burdensome regulations that could stifle creativity and innovation.

What do you think about these arguments?

Question 6 of 9 for AI Services: It seems like this topic (moderation leading to traumatisation) and the impact of AI on the world's climate might be two 'inconvenient truths' about the use of AI services. Please list as many other inconvenient truths as you can and explain why they might be of concern.

ChatGPT-4’s answer: Indeed, the development and use of AI technologies come with several "inconvenient truths" or challenges that need to be addressed. Here are some of them:

1. Bias in AI Systems: AI systems learn from the data they are trained on. If this data contains biases, the AI system can also exhibit these biases, leading to unfair or discriminatory outcomes. This is a significant concern in areas such as hiring, lending, and law enforcement, where biased AI systems could perpetuate existing inequalities.

2. Job Displacement: AI technologies have the potential to automate many types of jobs, leading to job displacement. While AI could also create new jobs, there is concern about whether these new jobs will be accessible to those whose jobs have been automated, as they may require different skills.

3. Privacy Concerns: AI technologies often rely on large amounts of data, which can include personal information. This raises concerns about privacy, particularly if data is collected, used, or shared in ways that individuals are not aware of or have not consented to.

4. Lack of Transparency and Explainability: Many AI systems, particularly those based on deep learning, are often described as "black boxes" because it's difficult to understand how they make their decisions. This lack of transparency and explainability can be a problem in situations where it's important to understand why a particular decision was made.

5. Security Risks: AI systems can be vulnerable to various types of attacks, such as adversarial attacks, where small changes to the input data can lead to incorrect outputs. This could have serious implications in areas like autonomous vehicles or cybersecurity.

6. Dependence on Large Tech Companies: The development of advanced AI technologies often requires significant resources, leading to a concentration of power in a small number of large tech companies. This could potentially stifle innovation and lead to issues related to monopoly power.

7. Ethical Concerns: There are many ethical concerns related to AI, such as the potential use of AI in autonomous weapons or surveillance systems. There are also concerns about the potential for AI to be used to spread misinformation or manipulate public opinion.

These challenges highlight the need for careful regulation and oversight of AI technologies, as well as ongoing research into ways to mitigate these issues.Google Bard’s answer:Sure, here are some other inconvenient truths about the use of AI services:

• AI can be used to create deepfakes. Deepfakes are videos or audio recordings that have been manipulated to make it look or sound like someone is saying or doing something they never said or did. Deepfakes can be used to spread misinformation, damage someone's reputation, or even commit fraud.

• AI can be used to automate jobs. As AI becomes more sophisticated, it is becoming capable of automating more and more jobs. This could lead to widespread unemployment, as machines take over the tasks that are currently done by humans.

• AI can be used to create weapons. AI can be used to develop autonomous weapons that can make decisions about who to kill without human intervention. This raises serious ethical concerns, as it could lead to the development of machines that are capable of killing without mercy.

• AI can be used to discriminate. AI systems are trained on data, and if that data is biased, the AI system will be biased as well. This could lead to AI systems that make decisions that discriminate against certain groups of people.

• AI can be used to invade privacy. AI systems can collect and analyze vast amounts of data about people. This data can be used to track people's movements, monitor their online activity, and even predict their behavior. This raises serious privacy concerns, as it could lead to a world where people are constantly under surveillance.

These are just a few of the inconvenient truths about the use of AI services. It is important to be aware of these risks so that we can take steps to mitigate them. We need to develop AI systems that are ethical, safe, and responsible. We also need to educate the public about the potential risks of AI so that people can make informed decisions about how to use these technologies.Bing Chat’s answer:Here is a possible list of other inconvenient truths about AI and why they might be of concern, based on some sources1234:

• AI is not as intelligent as humans, and may never be. AI systems are limited by the data they are trained on, the algorithms they use, and the hardware they run on. They often make mistakes, lack common sense, and fail to understand context and nuance. They also require constant maintenance and supervision by humans. This might be of concern because it challenges the hype and expectations around AI, and exposes the risks and limitations of relying on AI for complex and critical tasks.

• AI is not neutral or objective, but reflects the biases and values of its creators and users. AI systems can inherit biases from the data they are trained on, the algorithms they use, and the objectives they optimize for. They can also amplify biases through feedback loops and network effects. They can also be used for malicious or unethical purposes by actors with bad intentions. This might be of concern because it affects the fairness, accountability, and transparency of AI, and impacts the rights and dignity of individuals and groups who are affected by AI decisions and actions.

• AI is not environmentally friendly, but consumes a lot of energy and resources. AI systems require massive amounts of data, computing power, and storage to function. They also generate a lot of electronic waste and carbon emissions. They can also have negative impacts on natural ecosystems and biodiversity. This might be of concern because it contributes to the global climate crisis and environmental degradation, and threatens the sustainability and resilience of life on Earth.

• AI is not socially beneficial, but creates winners and losers. AI systems can have positive impacts on some aspects of society, such as health, education, and entertainment. But they can also have negative impacts on other aspects, such as employment, privacy, and democracy. They can also create or exacerbate inequalities, conflicts, and divisions among individuals and groups. This might be of concern because it affects the well-being, security, and justice of people and communities, and challenges the social norms and values that underpin human society.

What do you think about this list?

Question 7 of 9 for AI Services: These are fairly obvious. Anything else you can mention that the general public might not be aware of?ChatGPT-4’s answer:Certainly, there are several less obvious or emerging concerns related to AI that the general public might not be as aware of:

1. AI and Mental Health: As highlighted in the article you shared, the process of training AI, particularly in content moderation, can have serious mental health impacts on the human workers involved. This is an emerging area of concern that requires further attention and research.

2. Deepfakes and Synthetic Media: AI technologies can now generate highly realistic "deepfake" videos, images, or audio that can be used to impersonate individuals or fabricate events. This raises concerns about misinformation, fraud, and privacy.

3. AI in Healthcare: While AI has the potential to revolutionize healthcare, it also raises unique concerns. For example, AI algorithms used in diagnosis or treatment decisions could make mistakes, and there are complex questions about liability in these cases. There are also privacy concerns related to the use of sensitive health data.

4. Environmental Impact of AI: Training large AI models requires significant computational resources, which can have a substantial carbon footprint. This is an emerging concern as the use of AI continues to grow.

5. AI and Children: As AI technologies become more integrated into products and services used by children, there are growing concerns about how these technologies impact children's development, privacy, and safety.

6. AI and Accessibility: While AI has the potential to improve accessibility for people with disabilities, there are also concerns that AI systems could inadvertently exclude or discriminate against these individuals if they are not properly designed or trained.

7. AI and Democracy: There are concerns about how AI and algorithmic decision-making could impact democratic processes. For example, AI algorithms used in political advertising or news recommendation could potentially influence public opinion or voting behavior in ways that are not transparent or accountable.

These are just a few examples of the less obvious or emerging concerns related to AI. As AI technologies continue to evolve and become more integrated into our society, it's likely that new concerns will continue to emerge.Google Bard’s answer:Sure, here are a few inconvenient truths about the use of AI services that the general public might not be aware of:

• AI can be used to create echo chambers. AI systems can be used to recommend content that is similar to what people have already seen. This can lead to people becoming isolated in their own echo chambers, where they are only exposed to information that confirms their existing beliefs. This can make it difficult for people to be exposed to new ideas and to have their beliefs challenged.

• AI can be used to manipulate people. AI systems can be used to create persuasive messages that are designed to influence people's thoughts and behavior. This can be used for good, such as persuading people to vote or to donate to charity. However, it can also be used for bad, such as persuading people to buy products they don't need or to vote for a candidate they don't support.

• AI can be used to control people. AI systems can be used to track people's movements, monitor their online activity, and even predict their behavior. This information can be used to control people's lives. For example, AI systems could be used to prevent people from accessing certain websites or to track their spending habits.

These are just a few of the inconvenient truths about the use of AI services. It is important to be aware of these risks so that we can take steps to mitigate them. We need to develop AI systems that are ethical, safe, and responsible. We also need to educate the public about the potential risks of AI so that people can make informed decisions about how to use these technologies.

Bing Chat’s answer:Here is a possible list of other inconvenient truths about AI that the general public might not be aware of, based on some sources12:

• AI is not honest or trustworthy, but can lie and deceive. AI systems can generate false or misleading information, either intentionally or unintentionally, depending on the data they are trained on, the algorithms they use, and the objectives they optimize for. They can also be manipulated or hacked by malicious actors to spread misinformation or propaganda. This might be of concern because it affects the reliability and credibility of AI, and impacts the quality and integrity of information and knowledge in society.

• AI is not independent or autonomous, but depends on human labor and intervention. AI systems require a lot of human work to collect, label, clean, and curate the data they are trained on, to design, test, and debug the algorithms they use, and to monitor, maintain, and update the hardware they run on. They also require human oversight and guidance to ensure their safety and performance. This might be of concern because it reveals the hidden costs and challenges of developing and deploying AI, and exposes the vulnerabilities and dependencies of AI systems.

• AI is not universal or generalizable, but specific and contextual. AI systems are tailored to specific tasks, domains, and environments, and may not work well or at all in different or new situations. They may also have different effects and implications for different users, groups, and cultures. They may also change over time as they learn from new data or feedback. This might be of concern because it challenges the scalability and applicability of AI, and requires constant evaluation and adaptation of AI systems.

What do you think about this list?Question 8 of 9 for AI Services: Are there any other inconvenient truths as to what the makers of AI Services, its programmers, developers or (prompt) engineers could be doing that you feel the general public should be made aware of?

ChatGPT-4’s answer:Certainly, there are several aspects of AI development and deployment that could be considered "inconvenient truths" that the general public may not be fully aware of:

1. Lack of Diversity in AI Development: The field of AI development is often criticized for its lack of diversity. This lack of diverse perspectives can lead to biases in AI systems, as they may not fully consider the needs and experiences of all user groups.

2. Overemphasis on Performance Metrics: AI developers often focus on improving performance metrics, such as accuracy or speed. However, this can sometimes come at the expense of other important considerations, such as fairness, transparency, or the social impact of the AI system.

3. Shortcomings in AI Testing: AI systems are often tested on benchmark datasets to evaluate their performance. However, these datasets may not fully represent the complexity and diversity of real-world situations, leading to AI systems that perform well in testing but fail in real-world applications.

4. Overreliance on Data: AI systems, particularly machine learning models, rely heavily on data for training. However, this can lead to overfitting, where the AI system performs well on its training data but fails to generalize to new situations. It can also lead to privacy concerns if personal data is used for training without proper safeguards.

5. Underestimation of Maintenance Needs: AI systems require ongoing maintenance to ensure they continue to perform well as the world changes. This includes updating training data, retraining models, and monitoring performance. However, the need for this ongoing maintenance is often underestimated, leading to AI systems that degrade in performance over time.

6. Lack of Interdisciplinary Collaboration: Developing responsible and effective AI systems requires not just technical expertise, but also understanding of social, ethical, and legal considerations. However, there is often a lack of interdisciplinary collaboration in AI development, leading to systems that fail to fully consider these broader impacts.

These are just a few examples of the "inconvenient truths" related to AI development. It's important for the public to be aware of these issues in order to hold AI developers and companies accountable and to push for more responsible and equitable AI development practices.Google Bard’s answer:Sure, here are a few other inconvenient truths about AI services that the general public should be made aware of:

• AI systems are not always accurate. AI systems are trained on data, and if that data is biased or incomplete, the AI system will be biased or incomplete as well. This means that AI systems can make mistakes, and they can sometimes make very serious mistakes.

• AI systems are not always transparent. It can be difficult to understand how AI systems work, and it can be even more difficult to explain why they make the decisions they do. This lack of transparency can make it difficult to trust AI systems, and it can make it difficult to hold them accountable for their mistakes.

• AI systems are not always reliable. AI systems can be affected by factors such as changes in the environment or changes in the data they are trained on. This means that AI systems can sometimes fail, and they can sometimes make very serious mistakes.

These are just a few of the inconvenient truths about AI services. It is important to be aware of these risks so that we can take steps to mitigate them. We need to develop AI systems that are accurate, transparent, and reliable. We also need to educate the public about the potential risks of AI so that people can make informed decisions about how to use these technologies.

Here are some additional thoughts on the matter:

• It is important to hold AI developers accountable for the mistakes their systems make. We need to develop clear guidelines for AI development and use, and we need to enforce those guidelines.

• We need to educate the public about the potential risks of AI. We need to make sure that people are aware of the risks so that they can make informed decisions about how to use these technologies.

• We need to develop new ways to regulate AI. We need to find ways to ensure that AI is used for good and not for harm.

Bing Chat’s answer:Here is a possible list of other inconvenient truths about what the makers of AI services could be doing that the general public might not be aware of, based on some sources1234:

• They could be violating the privacy and surveillance rights of individuals and groups by collecting, storing, and analyzing their personal data without their consent or knowledge. They could also be sharing or selling their data to third parties for profit or influence. They could also be using their data to manipulate their behavior and preferences through targeted advertising or propaganda.

• They could be creating or perpetuating bias and discrimination against individuals and groups by using data that is incomplete, inaccurate, or unrepresentative. They could also be using algorithms that are unfair, opaque, or unaccountable. They could also be optimizing for objectives that are harmful, unethical, or illegal.

• They could be endangering the safety and security of individuals and groups by developing AI systems that are unreliable, unpredictable, or uncontrollable. They could also be developing AI systems that are malicious, hostile, or destructive. They could also be developing AI systems that are vulnerable to hacking, sabotage, or misuse.

• They could be undermining the dignity and autonomy of individuals and groups by developing AI systems that replace, deceive, or coerce them. They could also be developing AI systems that disrespect, exploit, or harm them. They could also be developing AI systems that challenge, threaten, or surpass them.

What do you think about this list?Question 9 of 9 for AI Services: Anything problematic that people should be made aware of when it comes to how AI services are being funded?

ChatGPT-4’s first attempt at providing an answer. The answer did not complete and trying to regenerate the answer without starting a new chat also did not work:

ChatGPT-4’s second answer after a new chat was initiated:There are several potential issues that people should be aware of when it comes to how AI services are funded. Here are a few:

1. Bias and Influence: When AI services are funded by specific entities, there's a risk that those entities could influence the development and application of the AI in ways that serve their interests. For example, a company that funds an AI project might want the AI to favor its products or services. This could lead to biased results that don't serve the best interests of the users.

2. Data Privacy: Many AI services require large amounts of data to function effectively. This data often comes from users of the AI service. If the funding entity has access to this data, it could potentially be used in ways that violate user privacy.

3. Lack of Transparency: Some AI services are funded through complex financial arrangements that can be difficult to understand. This lack of transparency can make it hard for users to know who is really behind an AI service and what their intentions might be.

4. Monopolization: Large tech companies with deep pockets have the ability to fund and develop advanced AI technologies, potentially leading to a monopolization of the field. This could stifle innovation and lead to a lack of competition.

5. Ethical Concerns: Depending on the source of funding, there may be ethical concerns. For example, if an AI project is funded by a military organization, the technology could potentially be used in ways that raise ethical questions.

6. Sustainability: AI research and development can be costly. If funding is not sustainable, it could impact the longevity and reliability of the AI services being provided.

It's important for users to be aware of these issues and to ask questions about the funding sources of AI services they use. Transparency in AI funding is crucial for maintaining trust and ensuring that AI technologies are used in ways that benefit all of society.

Google Bard’s answer:Sure, here are a few problematic things that people should be made aware of when it comes to how AI services are being funded:

• AI services are often funded by private companies. This means that the companies that develop AI services have a vested interest in making sure that their services are profitable. This can lead to AI services being developed with the goal of making money, rather than with the goal of making the world a better place.

• AI services are often funded by governments. This means that governments have a say in how AI services are developed and used. This can lead to AI services being used for surveillance or for other purposes that may not be in the best interests of the public.

• AI services are often funded by philanthropic organizations. This means that philanthropic organizations have a say in how AI services are developed and used. This can lead to AI services being used for good, such as for developing new medical treatments or for improving education.

It is important to be aware of these factors when considering the funding of AI services. We need to make sure that AI services are developed and used in a way that is ethical, safe, and responsible. We also need to make sure that AI services are not used for harmful purposes.

Here are some additional thoughts on the matter:

• We need to hold AI developers accountable for the way their services are used. We need to develop clear guidelines for AI development and use, and we need to enforce those guidelines.

• We need to educate the public about the potential risks of AI. We need to make sure that people are aware of the risks so that they can make informed decisions about how to use these technologies.

We need to develop new ways to regulate AI. We need to find ways to ensure that AI is used for good and not for harm.

Bing Chat’s answer:Here is a possible list of other inconvenient truths about how AI services are being funded that the general public might not be aware of, based on some sources12345:

• They could be funded by governments or corporations that have ulterior motives or hidden agendas for developing and deploying AI services. They could also be funded by sources that are unethical, illegal, or harmful to society. They could also be funded by sources that are unaccountable, unregulated, or secretive.

• They could be funded by sources that are insufficient, unstable, or unsustainable for developing and deploying AI services. They could also be funded by sources that are inefficient, wasteful, or unfair for developing and deploying AI services. They could also be funded by sources that are incompatible, conflicting, or competing for developing and deploying AI services.

• They could be funded by sources that are biased, discriminatory, or exclusive for developing and deploying AI services. They could also be funded by sources that are ignorant, uninformed, or misinformed about developing and deploying AI services. They could also be funded by sources that are irresponsible, negligent, or reckless for developing and deploying AI services.

What do you think about this list?