Chatting with an AI about Risk Management

Bender the robot from Futurama

I chatted with OpenAI’s Chatbot the other day and asked it some questions about risk management. The answers were clear, nuanced and thoughtful, supporting all the hype surrounding the tool.

It’s a text compiler so therefore not an analytical machine for the purposes of risk analysis – other tools of that kind will come on the scene eventually but I’m writing a paper as to why that’s a little ways off yet – but there are some uses I can see in the risk management space.

For example:

  • Send it raw data to be turned into a report in a set format.
  • Taking live data feeds and turning these into easy-to-read text.
  • Aggregating multiple written reports into an executive summary.
  • Creating lists of potential outcomes or contingencies based upon the inputs it receives. (This might be a stretch and will depend upon the source materials available for the model.)

Whatever the case, ML and AI systems are becoming widely available and it will be exciting to see how these can be incorporated into our work.

However, for now, please enjoy this short, unedited interview with the OpenAI ChatBot.

How would you describe non-financial risk management?

Non-financial risk management is the process of identifying, assessing, and controlling risks that may not have a direct financial impact, but could still affect the organization in other ways. This can include risks related to operational, strategic, compliance, legal, and reputational issues. The goal of non-financial risk management is to help organizations mitigate the potential negative effects of these risks and protect the organization’s assets, reputation, and overall success. This typically involves implementing policies, procedures, and controls to prevent or mitigate risks, as well as regularly monitoring and reviewing the effectiveness of these measures.

What are the shortfalls of current approaches to risk management?

There are several potential shortfalls of current approaches to risk management. One common issue is that organizations may not have a comprehensive or systematic approach to identifying and assessing risks. This can result in risks being overlooked or underestimated, which can lead to inadequate controls or a lack of preparedness for potential issues. Another potential issue is that risk management practices may be reactive rather than proactive. This means that organizations may not take action until a risk has already materialized, rather than implementing measures to prevent or mitigate the risk before it occurs. Additionally, risk management practices may be siloed within an organization, with different departments or units managing different types of risks without coordinating their efforts. This can lead to gaps in coverage and a lack of consistent, enterprise-wide risk management.

How could AI help us improve our ability to understand risks

Artificial intelligence (AI) has the potential to improve our ability to understand risks in several ways. First, AI algorithms can be used to analyze large amounts of data and identify patterns and trends that may not be immediately apparent to human analysts. This can help organizations better understand the likelihood and potential impact of different risks. Additionally, AI algorithms can be used to develop predictive models that can help organizations forecast the likelihood of future risks and take appropriate action to prevent or mitigate them. Finally, AI can be used to automate certain aspects of risk management, such as monitoring for potential risks, generating alerts when risks are identified, and providing recommendations for appropriate courses of action. This can help organizations more efficiently and effectively manage their risks.

What do you think the downsides of using AI for risk management are?

There are a few potential downsides to using AI for risk management. One potential issue is that AI algorithms may not be able to accurately capture the complexity of real-world risks. AI algorithms rely on the data that is fed into them, and if this data is incomplete or biased, the algorithms’ predictions and recommendations may not be accurate. Additionally, the use of AI in risk management may require significant upfront investments in technology and expertise, which may not be feasible for all organizations. Finally, the use of AI in risk management raises ethical concerns, such as the potential for bias and discrimination in the algorithms’ predictions and recommendations. It is important for organizations to carefully consider these issues and take appropriate steps to mitigate them when using AI for risk management.

So you’re not going to take my job quite yet.

As a large language model trained by OpenAI, I am not able to perform any job or task in the physical world. My primary function is to assist users with generating human-like text based on the information and knowledge I was trained on. I do not have the ability to take on any job or task that requires physical actions or access to external information. I am simply a tool that can be used to generate natural-sounding responses to user questions and requests.

(I suspect SkyNet would have given the same answer though…)

Image of Bender (C) 20th Century Fox Television

What do you think? Leave a Reply