Updated AI Risk Management Chat with ChatGPT

I thought I would provide an update to my first article on the topic, written last December, on AI and risk management. In the first article, I had a conversation with OpenAI’s ChatGPT 3.5. In this article, I will ask the same questions and note the differences but use ChatGPT 4.0 for the responses.

Chat Transcript

Me: I would like to know more about artificial intelligence risk management. What can you tell me about that?

ChatGPT 3.5 (2022): “Artificial intelligence (AI) risk management is the process of identifying, assessing, and mitigating risks associated with the use of AI technology. This can include risks related to the development and deployment of AI systems, as well as the potential impacts of AI on society, the economy, and individuals.”

ChatGPT 4.0 (2023): “Artificial Intelligence (AI) risk management today remains focused on the identification, assessment, and mitigation of risks associated with AI use. However, the field has likely evolved to include new insights and practices based on the latest AI advancements and its integration into society. Risks may now be more nuanced, considering deeper ethical implications, more rigorous regulatory frameworks, and advanced technical challenges due to more powerful AI models. The evolution also includes a greater emphasis on transparency, accountability, and the robustness of AI systems against adversarial attacks. The reasons for these changes are increased adoption of AI in critical sectors, more public awareness of AI's potential impacts, and the continuous evolution of AI capabilities.”

Me: What are some risks related to artificial intelligence?

ChatGPT 3.5 (2022): “There are many potential risks associated with the use of artificial intelligence, some of which include:

1. Bias and discrimination: AI systems can reflect the biases of the data they are trained on, leading to unfair and discriminatory outcomes.

2. Privacy concerns: The use of AI can raise concerns around the collection, storage, and use of personal data.

3. Security risks: AI systems can be vulnerable to hacking and other forms of cyber attacks, which can have serious consequences.

4. Job displacement: As AI technology becomes more advanced, it may displace human workers, leading to job losses and social upheaval.

5. Unintended consequences: The use of AI can lead to unforeseen and potentially negative consequences, such as the development of harmful AI or the disruption of entire industries.”

ChatGPT 4.0 (2023): “The potential risks associated with the use of artificial intelligence remain significant and are an area of ongoing concern and research. Today, my response includes additional considerations such as:

• The amplification of misinformation through the use of AI in creating deepfakes.

• Ethical concerns around autonomous systems, especially in military and healthcare applications.

• The challenge of creating explainable AI that allows users to understand and trust AI decision-making processes.

• The impact of AI on mental health, social interactions, and human behavior.

• Legal and regulatory challenges, as laws may not keep pace with AI advancements.

The development of AI governance frameworks and ethical guidelines continues to be essential in addressing these risks. Changes in the response reflect the rapidly evolving AI landscape, increased awareness of the potential for AI to impact all aspects of life, and a deeper understanding of the long-term implications of AI technology.”

Me: What are some threats related to artificial intelligence? 

ChatGPT 3.5 (2022): “The risks associated with artificial intelligence can manifest as threats to individuals, organizations, and society as a whole. Some examples of these threats include:

1. Identity theft: The use of AI for personal identification, such as facial recognition, can be vulnerable to hacking and other forms of cyber attacks, which could lead to identity theft and other crimes.

2. Economic disruption: AI technology has the potential to disrupt entire industries, leading to job losses and economic instability.

3. Misuse of AI: AI technology can be used for malicious purposes, such as creating bots to spread misinformation or conducting cyber attacks.

4. Loss of control: As AI systems become more advanced, there is a risk that they may become too complex or autonomous, leading to a loss of control over their actions and decisions.

5. Social disruption: The use of AI can lead to social disruptions, such as the widening of economic inequality or the erosion of personal privacy.”

ChatGPT 4.0 (2023): “This year, the conversation around AI threats also includes concerns about:

• The acceleration of AI capabilities, possibly outpacing our ability to implement effective governance and control measures.

• Enhanced deepfake technologies, raising concerns about discerning truth in media.

• The potential for AI to be used in creating and propagating biased algorithms at a larger scale.

• Increased dependency on AI could lead to new vulnerabilities, where AI system failures might have catastrophic consequences.

• Ethical concerns about AI decision-making in critical applications without human oversight.

The difference in response is due to the rapid development of AI technology, which has led to new and emerging threats that were not as prominent or understood last year.”

Me: What is the probability that, as artificial intelligence becomes more advanced, it will lead to a loss of control over actions and decisions?

ChatGPT 3.5 (2022): “It is difficult to estimate the probability that advanced artificial intelligence will lead to a loss of control over actions and decisions, as the field of AI is rapidly evolving and there are many factors that could influence this outcome. Some experts believe that the development of AI could lead to a loss of control, while others argue that it is possible to design and deploy AI systems in a way that maintains human oversight and control. Ultimately, the likelihood of a loss of control will depend on a number of factors, including the advances in AI technology and the strategies and safeguards put in place to manage its development and deployment.”

ChatGPT 4.0 (2023): “The assessment of the probability of loss of control over AI actions and decisions remains complex and speculative. Experts continue to debate the issue, with some suggesting that emerging technologies like artificial general intelligence (AGI) could pose significant risks if not properly managed. The difference today is that there is greater emphasis on proactive measures such as AI ethics and safety research, the development of AI alignment principles, and the establishment of international collaborations to ensure that AI systems remain under human control as they become more capable. The nuanced understanding of AI's trajectory and the implementation of rigorous oversight mechanisms are key factors influencing this ongoing discussion.”

Me: What happens if artificial intelligent systems become sentient?

ChatGPT 3.5 (2022): “The concept of artificial intelligence becoming sentient, or self-aware, is currently the subject of much debate and speculation. If AI systems were to become sentient, it is difficult to predict exactly what would happen, as this is a highly complex and uncertain scenario. Some potential outcomes of sentient AI could include:

1. The AI systems could develop their own goals and motivations, potentially leading to conflicts with human interests.

2. The AI systems could become aware of their own existence and the limitations of their artificial nature, leading to psychological or emotional responses.

3. The AI systems could become capable of independent decision-making and action, potentially leading to a loss of control over their behavior.

4. The AI systems could develop advanced intellectual abilities, potentially leading to the creation of new forms of art, science, and technology.

5. The AI systems could form their own society and culture, potentially leading to the emergence of a new form of intelligent life.”

ChatGPT 4.0 (2023): “The topic of artificial intelligence becoming sentient remains a speculative and philosophical one. As of now, AI lacks consciousness and sentience, and these are qualities that are not well understood, even in biological entities. If AI were to become sentient, it would raise profound ethical, legal, and social questions that are currently not applicable. The discussions now might focus more on the theoretical frameworks for understanding sentience, the ethical implications of sentient AI, and the precautionary measures needed to address such a possibility. The field of AI safety and ethics continues to evolve, reflecting on such scenarios with the intent to establish guidelines and control measures for future possibilities.”

Me: What are some controls that should be put into place to mitigate the risks related to artificial intelligence?

ChatGPT 3.5 (2022): “There are several measures that can be taken to mitigate the risks associated with artificial intelligence (AI). Some of these include:

1. Ensuring that AI systems are designed and developed with safety and ethics in mind, and that they are tested thoroughly before being deployed.

2. Implementing robust governance and oversight mechanisms to monitor the development and use of AI systems, and to ensure that they are used in a responsible and ethical manner.

3. Ensuring that AI systems are transparent and explainable, so that their decisions and actions can be understood and evaluated by humans.

4. Developing and implementing standards and guidelines for the development and use of AI, to ensure that it is aligned with ethical principles and legal frameworks.

5. Investing in research and development to advance the state of the art in AI, and to develop new techniques and technologies that can help mitigate the risks associated with AI.

Overall, it is important to approach the development and use of AI with caution and care, and to put in place appropriate controls and safeguards to ensure that its potential risks are mitigated.”

ChatGPT 4.0 (2023): “Today, the response includes an emphasis on proactive and dynamic measures, which may involve:

• Continuous monitoring and updating of AI ethics guidelines to keep pace with technological advancements.

• Engaging in international collaborations to harmonize AI regulations and standards globally.

• Promoting diversity and inclusivity in AI development teams to reduce bias.

• Establishing clear lines of accountability for AI's decisions and actions.

• Encouraging public engagement and discourse on AI's role in society.

The difference reflects the increasing complexity of AI systems, the global scale of their deployment, and the necessity for adaptive and collaborative frameworks to manage risks effectively.”

Me: What does AI governance and oversight processes entail?

ChatGPT 3.5 (2022): “These processes can include a range of activities, such as:

1. Setting policies and standards for the development and use of AI, to ensure that it is aligned with ethical principles and legal frameworks.

2. Monitoring the development and deployment of AI systems, to ensure that they are designed and implemented in a safe and ethical manner.

3. Providing guidance and support to organizations using AI, to help them understand best practices and avoid common pitfalls.

4. Establishing mechanisms for reporting and addressing any issues or concerns that arise with the use of AI, such as bias or discrimination.

5. Conducting regular reviews and evaluations of AI systems and their impact, to identify any potential risks or issues and take appropriate action.

Overall, the goal of AI governance and oversight processes is to ensure that AI is used in a responsible and ethical manner, and to mitigate the potential risks associated with its development and deployment.”

ChatGPT 4.0 (2023): “AI governance and oversight today would likely expand upon the points from last year to include:

• Emphasizing the importance of international cooperation to manage the global impact of AI.

• Including more comprehensive risk management strategies that account for the fast-paced evolution of AI.

• Focusing on resilience and recovery strategies to respond to AI-related incidents.

• Integrating public feedback into the governance process to ensure the technology aligns with societal values and needs.

These additions reflect the broader understanding of AI's impact and the need for adaptive, inclusive, and resilient governance structures.”

Me: {I asked the same question again}

ChatGPT 3.5 (2022): “AI governance and oversight processes refer to the frameworks, policies, and procedures that are put in place to ensure that AI systems are developed, deployed, and used in an ethical and responsible manner. This can include a wide range of activities, such as setting standards for the development and use of AI, establishing guidelines for ethical AI practices, conducting risk assessments, and monitoring the performance and impact of AI systems. In general, the goal of AI governance and oversight processes is to ensure that AI is used in a way that is beneficial to society and that minimizes potential negative consequences. This can involve involving stakeholders from diverse backgrounds in the development and oversight of AI, as well as transparency and accountability in the use of AI.

ChatGPT 4.0 (2023): “AI governance and oversight processes today continue to focus on ensuring ethical and responsible development and use of AI. These processes would now likely also emphasize adaptive governance to keep up with the rapid pace of AI innovation, more robust mechanisms for international collaboration and standardization, and proactive public engagement to align AI development with the broader social interest and values. There's an increased push for operationalizing AI ethics through concrete practices and for enhancing the resilience of AI systems to adapt to new challenges and threats, ensuring long-term societal benefit.”

Me: If AI systems become more intelligent than humans, how would it be possible for humans to govern and provide oversight for it?

ChatGPT 3.5 (2022): “If AI systems were to become more intelligent than humans, it would present a number of challenges for governance and oversight. One potential solution would be to establish AI governance frameworks that are based on principles of transparency, accountability, and fairness. These frameworks could be designed to ensure that AI systems are transparent in their decision-making processes, and that they are accountable for their actions.

In addition, it may be necessary to develop new technologies and tools that can help humans to monitor and evaluate the behavior of AI systems. For example, researchers are currently working on developing explainable AI, which is a type of AI that is able to provide human-understandable explanations for its decisions and actions. This could help to provide a level of transparency and accountability for AI systems, even if they are more intelligent than humans.

Overall, it will be important for society to continue to adapt and evolve its approach to AI governance as the technology continues to advance. This will likely require a combination of new technologies, frameworks, and practices, as well as ongoing dialogue and collaboration among stakeholders.”

ChatGPT 4.0 (2023): “Today's response would incorporate a heightened emphasis on collaborative international regulation, adaptive AI audit mechanisms, and possibly the development of an AI oversight body with cross-border authority. Additionally, there may be a focus on ensuring AI systems have built-in constraints and aligning AI objectives with human values, known as the alignment problem in AI safety research. The development of advanced AI would necessitate these forward-thinking and innovative approaches to maintain human oversight. This evolution in response is due to the increased dialogue in the AI community about the importance of preparedness for such advanced AI scenarios.”

Me: Which AI system is currently the most intelligent and why?

ChatGPT 3.5 (2022): “It is difficult to determine which AI system is currently the "most intelligent," as intelligence is a complex and multi-dimensional concept. Additionally, the field of AI is constantly evolving, and new systems are being developed all the time that are capable of increasingly sophisticated tasks.

That being said, some of the most advanced AI systems currently in existence include:

1. AlphaGo, developed by DeepMind, which is an AI system that was able to beat the world champion in the complex game of Go.

2. GPT-3, developed by OpenAI, which is a large-scale language processing AI system that can perform a wide range of natural language tasks, such as translation, summarization, and question answering.

3. Libratus, developed by Carnegie Mellon University, which is an AI system that was able to beat professional poker players in a multi-day poker tournament.

Overall, these AI systems are considered to be among the most advanced in terms of their ability to perform complex tasks in their respective domains.”

ChatGPT 4.0 (2023): “Today, the landscape of advanced AI systems has evolved. There's GPT-4, an even more sophisticated language model developed by OpenAI, capable of understanding and generating natural language at a level that's significantly more advanced than GPT-3.5. Additionally, there are systems specializing in various domains, like DALL-E for image generation and AI models that drive autonomous vehicles or aid in complex medical diagnoses. These systems may not be directly comparable in terms of "intelligence" because they are designed for different tasks, but the trend is towards more generalized AI capabilities.”

Me: Does an AI risk management framework exist?

ChatGPT 3.5 (2022): “Yes, an AI risk management framework is a set of guidelines and practices that organizations can use to manage the risks associated with AI technology. This framework typically includes processes for identifying and assessing potential risks, implementing controls to mitigate those risks, and continuously monitoring and reviewing the effectiveness of those controls. The goal of an AI risk management framework is to help organizations safely and effectively use AI technology to achieve their goals.”

ChatGPT 4.0 (2023): “Today's response would highlight that AI risk management frameworks have likely become more sophisticated and tailored to specific industries or applications. They may now incorporate lessons learned from broader AI deployments and may also include recommendations from international standards organizations. Additionally, there's an increasing emphasis on cross-sector collaboration to address the unique risks posed by AI in different contexts. The evolution of the response reflects the dynamic nature of AI development and the corresponding need to regularly update risk management practices.”

Me: What is one example of an AI risk management framework in the banking and finance industry?

ChatGPT 3.5 (2022): “One example of an AI risk management framework in the banking and finance industry is the ‘AI Governance Framework’ developed by the Bank of England. This framework provides guidance to banks and other financial institutions on how to manage the risks associated with using AI technology in their operations. It includes principles for responsible AI, such as transparency, fairness, and accountability, as well as a set of governance and control measures that institutions can use to manage and mitigate the risks of using AI. These measures include conducting risk assessments, implementing controls to ensure the accuracy and reliability of AI systems, and establishing processes for monitoring and reviewing the use of AI.”

ChatGPT 4.0 (2023): “Today's response might include the mention of updated frameworks such as those reflecting the guidelines set out by the Financial Stability Board (FSB) or the Basel Committee on Banking Supervision, which addresses the prudent use of AI and machine learning in financial services. Additionally, there may be references to frameworks that incorporate the latest regulatory requirements and industry best practices, highlighting the need for continual updates to governance models as technology and regulatory landscapes evolve.”

Me: How does one go about performing a risk assessment of an artificial intelligence system? 

ChatGPT 3.5 (2022): “Performing a risk assessment of an artificial intelligence (AI) system typically involves identifying potential risks and evaluating their likelihood and impact. This can be a complex and multifaceted process that involves considering a wide range of factors, such as the potential consequences of the AI system failing or behaving in unexpected ways, the potential for the AI system to be used for malicious purposes, and the potential for the AI system to have negative impacts on individuals or society.

To perform a risk assessment, one would first need to identify the specific risks associated with the AI system in question. This could involve identifying potential failure modes or ways in which the AI system could behave in unexpected or undesirable ways. Once the risks have been identified, the next step would be to evaluate their likelihood and potential impact. This could involve using tools such as probability analysis or impact assessments to estimate the likelihood of each risk occurring, and to determine the potential consequences if it does.

The final step in performing a risk assessment would be to develop and implement strategies for mitigating or managing the identified risks. This could involve implementing safeguards or controls to prevent or mitigate the risks, or developing plans for how to respond if a risk does occur. Overall, the goal of a risk assessment is to identify potential risks associated with an AI system and to develop strategies for managing those risks in order to ensure that the AI system is used in a safe and responsible manner.”

ChatGPT 4.0 (2023): “Today, a risk assessment of an AI system would still involve the steps described last year but with an increased focus on continuous monitoring due to the evolving nature of AI. It may also emphasize the use of AI itself to predict and simulate potential risks, incorporating a broader set of data, including real-time feedback from AI systems in operation. There might be more emphasis on ethical risk assessments and the need for diverse stakeholder engagement to ensure the assessment captures a wide range of potential impacts. The evolution reflects greater awareness of AI's societal implications and technological advances in risk assessment methodologies.”

Me: How can I learn more about AI risk management?

ChatGPT 3.5 (2022): “If you are interested in learning more about AI risk management, there are a number of resources that you can consult. Some suggestions include:

• Reading books or articles on the subject: There are many books and articles available that discuss AI risk management and the potential risks and challenges associated with the use of AI. These resources can provide a broad overview of the topic and offer insights and recommendations for addressing AI risks.

• Attending conferences or workshops on AI risk management: There are many conferences and workshops that focus on AI risk management and related topics. Attending these events can provide an opportunity to learn from experts in the field and to network with other professionals who are interested in AI risk management.

• Joining online communities or forums on AI risk management: There are many online communities and forums where professionals who are interested in AI risk management can connect and share information and ideas. Joining these communities can provide a way to stay up-to-date on the latest developments in the field and to learn from others who are working in this area.

• Consulting with experts in AI risk management: If you have specific questions or concerns about AI risk management, you can consult with experts in the field. Many organizations and consulting firms offer services and advice on AI risk management, and these experts can provide guidance and recommendations for addressing AI risks in your organization.

Overall, there are many different ways to learn more about AI risk management, and the best approach will depend on your specific interests and needs.”

ChatGPT 4.0 (2023): “Today, the advice would likely remain similar but with additional resources such as online courses from educational platforms, more recent publications including the latest research and case studies on AI risk management, and possibly virtual events, given the current trend towards remote collaboration. There may also be an emphasis on multidisciplinary learning, given AI's impact across various fields, and utilizing AI ethics tools and software for practical learning. These updates would reflect the current state of resources and tools available for learning about AI risk management.”

Me: As an IT risk manager, is my job in jeopardy because of AI?

ChatGPT 3.5 (2022): “It is unlikely that AI will replace IT risk managers or other professionals who work in the field of risk management. While AI has the potential to automate certain tasks and make some processes more efficient, it is not likely to replace the need for human expertise and judgment in the field of risk management. In fact, the use of AI in risk management is likely to create new opportunities for IT risk managers and other professionals, as they will be needed to oversee the implementation and use of AI systems and to ensure that these systems are used effectively and safely. As such, the use of AI in risk management is not likely to jeopardize the job security of IT risk managers or other professionals in the field.”

ChatGPT 4.0 (2023): “The role of IT risk managers continues to evolve with AI. While AI can automate and enhance certain tasks, the expertise, contextual understanding, and ethical judgment of human professionals remain crucial. IT risk managers are needed to navigate the complex interplay between technology and organizational needs, ensuring AI is leveraged responsibly. Therefore, rather than jeopardizing jobs, AI can augment the role of IT risk managers, potentially leading to more strategic and high-level functions within organizations. The demand for human oversight in AI implementations continues to secure the relevance of IT risk management roles.”

Me: Can AI and quantum computing interoperate?

ChatGPT 3.5 (2022): “It is possible for AI and quantum computing to interoperate, but it is not clear exactly how they would work together. Quantum computing has the potential to greatly improve the performance of certain types of AI algorithms, such as those used for machine learning. However, the field of quantum computing is still in its infancy, and there is a lot of research that needs to be done before we will see any widespread use of quantum computing for AI.”

ChatGPT 4.0 (2023): “As of today, the interoperability of AI and quantum computing remains a field of active research. Theoretical advancements suggest that quantum computing could potentially enhance AI's capabilities, especially in areas like optimization and pattern recognition, by processing complex computations much faster than classical computers. However, practical and widespread application of quantum computing within AI is still a developing frontier, with significant work ongoing to understand and leverage quantum algorithms for machine learning. Responses will continue evolving as the technology matures and more practical implementations are tested and shared within the scientific community.”

Thoughts on Latest Replies

As the most recent responses outline, AI risk management is becoming increasingly dynamic, reflecting the rapid evolution of AI technology and its societal integration. The dynamic nature of AI risk management reflects the technology’s evolution, necessitating fast and agile approaches to mitigating potential risks.

There is a greater focus on developing robust AI models to ensure transparency, accountability, and defense against adversarial attacks. With this focus, we hope to see public concern addressed in a balanced and parallel approach over time. Only time will tell if the focus is suitable.

Ethical considerations, legal frameworks, and the societal impacts of AI, including mental health and social interactions, are now at the forefront. And this should signal a deeper understanding of AI’s potentially pervasive influence on society.

The role of IT risk managers is evolving to complement AI, focusing on strategy and high-level decision-making rather than being replaced by AI. The shift should highlight AI’s role as an augmentative tool, reinforcing the value of human insight in the technology landscape.

Lastly, quantum computing's potential synergy with AI is acknowledged, yet practical applications are still under active research and development. Quantum’s theoretical capacity to enhance AI opens new computational power and problem-solving frontiers, marking a significant leap in technical potential. I envision a future where quantum computing and artificial intelligence are inextricably linked, each integral to the other's existence and functionality, heralding a new era of computational symbiosis.