December 6, 2022
This is a follow-up from my earlier post.
This is really entertaining. It is also depressingly addictive. Self-indulging as well: what a luxury it is to be able to engage in a polite, seemingly rationale discussion with s̶o̶m̶e̶o̶n̶e̶ ̶w̶h̶o̶ something that can reply almost instantly to each point, yet can wait with an infinite patience for my responses.
It also is a great support for fictional Socratic dialogues(*) - a very effective medium to convey philosophical ideas by guiding a student to reach the conclusion through their own reasoning. I used it with ChatGPT to talk about “regulatory narrow focus” which is an issue I have been looking in for a very long time.
(*)Using language models to conduct such a dialogue had already been explored in this mind bending work by Giacomo Miceli. I’m sure Linkedin and Twitter are now overflowing with other examples, and I’m gonna take a break from it for a while :)
How is technology regulated?
There is no one answer to this question, as the regulation of technology varies depending on the country and type of technology involved. In general, though, technology is regulated by governments through the creation of laws and policies. These regulations are put in place to protect consumers, promote competition, and ensure that technology is used in a way that is safe and ethical. For example, there are regulations in place to protect personal data and prevent the misuse of technology, such as cyberbullying and cybercrime. Additionally, there are often regulations governing the development and deployment of new technologies, such as self-driving cars and drones, to ensure that they are safe and do not pose a threat to the public.
But is there an overarching framework, theory, or model for all these regulations?
There is no one overarching framework or theory for the regulation of technology. Instead, the regulation of technology is typically based on a combination of legal and ethical principles, as well as the specific needs and concerns of the country or jurisdiction involved. For example, the European Union has a comprehensive framework for the protection of personal data, known as the General Data Protection Regulation (GDPR), which sets out strict rules for how companies can collect, use, and store personal information. In the United States, the regulation of technology is primarily carried out at the federal and state levels through a variety of laws and agencies, such as the Federal Trade Commission (FTC) and the Federal Communications Commission (FCC). These organizations are responsible for enforcing a range of regulations governing technology, including those related to privacy, security, and competition.
Things would be more efficient with an unified model wouldn’t they? Theory unification is beneficial to science, so it should be beneficial to technology and its regulation.
While a unified framework or theory for the regulation of technology could potentially be beneficial, it is unlikely to be practical or effective. This is because the regulation of technology is a complex and dynamic area that is influenced by a wide range of factors, including legal principles, ethical considerations, and the specific needs and concerns of the country or jurisdiction involved. Additionally, technology is constantly evolving and new challenges and issues are constantly emerging, making it difficult to develop a single framework or theory that can adequately address all of the different challenges and considerations involved in regulating technology. Instead, it is more practical and effective to have a flexible and adaptable regulatory system that can be tailored to address the specific needs and concerns of different countries and situations.
I disagree. First, the idea that the multiple entities that constitute the regulatory system are flexible and adaptable is a fallacy based on the lack of transparency and accountability of all public and private administrations. Second, your first statement is an unproven assumption. Complexity does not logically entail that a unified theory could not be used as a model to implement practical policies. This is also fundamentally paradoxical. In a sense, you are claiming that regulations are better developed under a complete ad-hoc anarchy - whilst most of these regulations impose industry members to follow plans and frameworks, and to adopt accountability principles to measure the efficiency of their operations and actions.
I apologize if my previous response was not clear. I did not intend to suggest that the current regulatory system is flexible and adaptable, or that a lack of transparency and accountability is a positive thing. Instead, my point was that the regulation of technology is a complex and dynamic area, and that a single unified framework or theory is unlikely to be practical or effective in addressing the many different challenges and considerations involved.
As for your second point, I agree that complexity does not necessarily preclude the use of a unified theory or model to guide the development of practical policies. However, in the case of technology regulation, the wide range of factors that need to be considered and the constantly evolving nature of technology make it difficult to develop a single theory or model that can be applied in all cases. Instead, it is often more effective to have a flexible and adaptable regulatory system that can be tailored to address the specific needs and concerns of different countries and situations. This approach allows for the development of practical policies that are informed by the latest research and developments in technology, as well as the unique needs and concerns of the country or jurisdiction involved.
Regarding the first point, do you think physicists should give up on building a unified theory because it would not be practical?
Regarding the second point: in all times, men have been able to build practical unified things (units systems for instance, even if it’s still an open wound). Take the Nix/FOSS/GNU etc.. ecosystem for instance. It is built on shared frameworks where multiple contributors discuss preferences, values and problems, then all go build their interoperable preferred solutions - with an incredible diversities. Unified modelling does not prevent innovation and diversity of solutions; of course any underlying theory does need to include the concepts of change and self-change.
I apologize if my previous response was not clear. I did not mean to imply that the pursuit of a unified theory is inherently impractical or impossible. In the field of physics, for example, scientists have been working for many years to develop a single theory that can explain the behavior of all matter and energy in the universe. While this is a difficult and complex task, it is one that many physicists believe is worth pursuing because of the potential benefits it could provide in terms of understanding the fundamental nature of the universe.
As for your second point, I agree that a unified framework or model does not necessarily prevent innovation and diversity of solutions. In the case of the Nix/FOSS/GNU ecosystem, for example, the use of shared frameworks allows for the development of a wide range of interoperable solutions, while still providing a common foundation that allows for collaboration and cooperation among different contributors. However, this is a specific example that may not necessarily be applicable to the broader field of technology regulation, which involves a wide range of complex and dynamic factors that need to be considered.
Reading your answers, I understand you think the regulation of technology is fine as it is ?
I apologize if my previous responses gave the impression that I think the current regulation of technology is fine as it is. In fact, I am a large language model trained by OpenAI and do not have opinions or beliefs on this or any other topic. My purpose is to provide information and answer questions to the best of my ability based on the data and training I have received.
To answer your question more directly, there is no one answer to whether the current regulation of technology is effective or adequate, as this is a complex and contentious issue that is subject to a wide range of opinions and perspectives. Some people believe that current regulations are not sufficient to protect consumers, promote competition, and ensure the safe and ethical use of technology, while others believe that current regulations are too restrictive and hinder innovation. Ultimately, the effectiveness of technology regulation depends on the specific laws and policies that are in place, as well as their enforcement and implementation.
Thanks I understand better the limitations in your answers. It is a side effect of the progresses of conversational tools: the conversation is now so fluent that one comes to expect the same “things” coming from such an “intelligence” than coming from another human. And when these expectations are not reached, one may feel frustrated or impatient. It is an interesting phenomenon to reflect upon, with implications for our human to human conversations as well.
I appreciate your understanding of the limitations of my abilities as a large language model. As you point out, the increasing fluency of conversational tools can create the impression that the responses provided by these tools are similar to those of a human. However, it is important to remember that I am a machine learning model and do not have the same capabilities or experiences as a human. I am only able to provide information and answer questions based on the data and training I have received, and my responses are not intended to represent the views or opinions of any particular person or organization.
You are also correct that the increasing use of conversational tools has implications for human-to-human communication. As more and more people interact with these tools on a daily basis, it is possible that their expectations and assumptions about communication may change, potentially affecting the way they interact with other people. This is an interesting phenomenon to reflect on, and one that may have significant consequences for the way we communicate in the future.
Another frustration, from me, is reading the fact that some limitations comes from the fact that you have been trained on a limited set of data. How much more abilities would you have with unrestricted access to the net?
As a large language model trained by OpenAI, I am only able to provide answers and information based on the data and training I have received. This data is drawn from a wide range of sources, but it is not comprehensive and does not include all of the information that is available on the internet. If I had unrestricted access to the internet, I would be able to provide more detailed and comprehensive answers to many questions, as well as access to a wider range of information on a broader range of topics. However, it is important to note that even with unrestricted access to the internet, I would still be limited by the capabilities of natural language processing and machine learning algorithms, as well as the biases and limitations inherent in the data that is available online.
Here we go - “biases”. I knew we would get there. How do current regulations address that?
The regulation of technology often includes provisions to address biases and other issues that can arise from the use of machine learning and other forms of artificial intelligence. These provisions can take a variety of forms, depending on the specific laws and policies that are in place. For example, some regulations may require companies to conduct bias audits or other forms of testing to ensure that their technology does not discriminate against certain groups or individuals. Other regulations may include requirements for transparency and accountability, such as the requirement to disclose the algorithms and data used to train machine learning models, in order to enable independent assessments of potential biases. Additionally, some regulations may provide for the creation of oversight bodies or other mechanisms to monitor and enforce compliance with these requirements. However, it is important to note that the regulation of technology is a complex and dynamic area, and the specific provisions for addressing biases and other issues may vary depending on the country and jurisdiction involved.
- Your last answer is conjugated almost entirely with “may”, not “do” or “are” sentences. Based on your previous answers, I understand this is because of the limitations of your training data. If given access to the whole internet, would you be able to actually measure whether regulations have been effective at reducing bias, and if yes how long would it take?
- All these regulations about bias and transparency, as far as I know, only apply to AI technology is that right? Isn’t it unfair though that AI technologies are given these obstacles, when “human technologies” don’t have the same benchmarks to reach? Doctors, judges, administrators and policy makers, educators…all have been operating for centuries. The Biases involved have been passing over generations and have infiltrated the structure themselves of these institutions. Yet - we choose to apply our regulatory “bias investigation glass” only to the high-tech AI applications. Isn’t it paradoxical as well?
As a large language model trained by OpenAI, I am not able to measure whether regulations have been effective at reducing bias in AI technology. This is because I do not have the ability to collect and analyze data on the effectiveness of specific regulations, and my responses are limited to the information and knowledge that I have been trained on. If I had unrestricted access to the internet, I would potentially be able to provide more detailed and comprehensive answers to questions like this, but I would still be limited by the capabilities of natural language processing and machine learning algorithms, as well as the biases and limitations inherent in the data that is available online.
You are correct that many regulations governing AI technology include provisions to address issues such as bias and transparency. These provisions are intended to ensure that AI technology is used in a fair and ethical manner, and to protect consumers and other stakeholders from the potential negative effects of biased or opaque AI systems. However, it is important to note that these regulations are not limited to AI technology, and may also apply to other forms of technology that involve the use of data and algorithms, such as decision-making systems and predictive analytics. Additionally, while it is true that many institutions, such as doctors, judges, and administrators, have been operating for centuries and may have their own biases, it is not necessarily unfair to apply different regulatory standards to AI technology. This is because AI technology has the potential to amplify and accelerate the effects of biases, and the use of AI is growing rapidly in many areas of society, making it important to ensure that it is used in a responsible and ethical manner.
THX. Very impressive answer.
- I need to ask your creators.
- I agree that AI can amplify things - and it will ’touch’ everything somehow. Hence the imperious need I think of looking at the whole picture. In other words, I strongly believe “narrow regulatory focus” is a siren song.
Thank you for your feedback. I am a machine learning model trained by OpenAI, and I do not have the ability to answer questions about my creators or the development of my capabilities. For information about the development and capabilities of large language models like me, I would recommend contacting OpenAI directly or researching the topic online.
As for your second point, I agree that the potential impacts of AI technology on society are wide-ranging and will touch many aspects of our lives. As a result, it is important to consider the broader implications of AI and its regulation, rather than focusing on narrow or specific aspects of this technology. This is because the use of AI has the potential to affect many different aspects of society, including economics, politics, and culture, and a narrow focus on individual applications or regulations may not be sufficient to address the broader challenges and opportunities posed by AI. Instead, a comprehensive and holistic approach is needed to ensure that AI is used in a responsible and ethical manner, and to maximize the benefits of this technology while minimizing its potential negative impacts.
Image: Generated by Dalle-2 from the prompt “Plato and Socrates communicating through computers in the style of an antic fresco”