We have been building OR-DA algorithms for decision support. For me, these are "co-pilots". They are used for decision-making by car dealers in the USA because we tailored the models for this industry (our system is https://www.frogdata.com/).
So one answer to "How can a co-pilot for decision making provide value for the business professionals making such decisions?" is that it provides the decision-maker with the embedded intelligence of an OR-DA practitioner who has learned by immersion in the business context, and that gets updated as we (the system providers) find ways to improve it.
Using LLM for these business decision agents is non-trivial. Think of it this way:
1. It's a known category of problem, and an optimal solution exists. This would use classical OR-DA.
2. It's a new category or an unsolved problem. When used in a business context, it is stated as developing situation awareness (akin to battlefield awareness) and then path-finding in explore/exploit cycles. Again, classical methods provide firm guides for both awareness (including anomaly detection) and experiment-assessment cycles.
If we include LLMs in the decision-support algorithm, the analytics practitioner is still required to build it. That practitioner can use an LLM as a co-pilot. Analytics practitioners acting as Decision Coaches (h/t Dr. Barrager and Dr. Milne) would also have a role to play in helping business decision-makers use the decision co-pilots because of the range of concerns to be handled. Those Decision Coaches could use an LLM as a co-pilot. So there are three kinds of LLM-co-pilots here:
1. Decision Co-Pilot = classical OR-DA co-pilots used by business decision-makers, augmented by LLM only where appropriate.
2. Decision Co-Pilot Maker = LLM to help the Decision Co-Pilot builder (an OR-DA practitioner). Such a Maker can democratize the role of analytics practitioners.
3. Decision-Coach Co-Pilot = LLM to guide the Decision Coach (an OR-DA practitioner) who helps business decision-makers use the Decision Co-Pilot.
Are we getting to the point of having an INFORMS BoK LLM that could serve these three uses?
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Rahul Saxena
FrogData.com
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Original Message:
Sent: 05-15-2023 04:39
From: Segev Wasserkrug
Subject: Can Decision Making benefit from an AI driven co-pilot?
Many thanks for the great comments!
Can you perhaps think of concrete examples of where such a co-pilot can help you as an analytics practitioner?
For example, think if we could ask for a first draft of a presentation that explains the analysis results in terms that would be understandable to the business person who is trying to solve the problem, and is adapted to the specific problem, and have such a first draft ready in minutes. Wouldn't this be great? Any other examples?
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Segev Wasserkrug
Research Staff Member
IBM Research - Israel
Haifa
Original Message:
Sent: 05-10-2023 10:15
From: Segev Wasserkrug
Subject: Can Decision Making benefit from an AI driven co-pilot?
Friends,
The Vice President and CEO of Innovation at Microsoft, Jason Wild, predicted that every job will be transformed by an existence of an AI co-pilot, driven by large language models (LLMs) such as ChatGPT (see Microsoft: Every job will have an artificial intelligence copilot). Microsoft is already driving such a transformation by infusing ChatGPT technologies into office - see Microsoft co-pilot for work).
When applying OR/analytics to solve real world problems, there are two fundamental roles: The business professional who makes the decision, and the OR/Analytics professional.
This got me thinking about the following questions: Can co-pilots for decision making, created by combining LLMs and OR techniques, and targeting these two roles, also transform the way decisions are made? How can a co-pilot for decision making provide value for the business professionals making such decisions? Can a co-pilot be created, to, for example, guiding analytics professionals in applying OR by, for example, walking them through the INFORMS CAP methodology in the context of the specific application? What other features should such co-pilots provide?
For a couple of initial examples of how LLMs can be used in the context of decision making, see some of my experiments in using ChatGPT to create optimization models starting from minute 19 of the video here and ChatGPT Does Decision Intelligence for Net Zero).
Would love to hear your feedback!
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Segev Wasserkrug
Research Staff Member
IBM Research - Israel
Haifa
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