How do I make the right decision – and how does AI help?

Example: Who is the right mentor for me?

Without IT support: The decision is based on the very limited information available to me: Who do I know, who is where in the hierarchy, who seems open, who do I dare to approach? These aren’t really the right characteristics for finding a good mentor, just those who are readily available.

With AI with machine learning: Depending on which mentor everyone else wanted (everyone or everyone with similar characteristics to me), I get a mentor with the same characteristics as popular mentors.

I don’t find out what other people’s decisions are based on. The fact that the decision criteria also apply to me – and that they are even useful for finding a good mentor – would be a really happy coincidence, which is unlikely.

So how can AI support good decisions?

From our point of view, the following ingredients are needed:

1. You have to understand the problem and first think about which criteria make sense for the decision. This has nothing to do with AI, but rather with common sense and psychological expertise.

2. When defining good decision criteria, it helps to include diverse perspectives. Just because it may be important to me that my mentor is in the same place as me, it may not matter to others.

3. The decision-making problem is broken down into individual small decisions. Instead of “Who is the right mentor for you”, you ask a series of questions, e.g. “Where would you like to meet your mentor?”, “What professional background should your mentor have?”, etc.

4. These individual questions are put to the participants. Only they can answer them in a way that will have the greatest possible impact for themselves. Since these are manageable decisions, where the impact is completely transparent and the participants are in control, this creates a perfect basis for a good decision – we call this preferences.

5. Algorithms ensure that simultaneous optimization takes place across the entire group of mentors and mentees. In other words, that everyone is suggested the person who is the best fit based on all mutual preferences. A game-theoretic optimum is created.

6. The resulting match is displayed with all the information on the underlying decision criteria.

7. In this way, the AI takes away the tedious search work and the participants can make an informed decision based on their individual situation.

The end result is the realization that AI can not only automate decisions, but also significantly improve them – if it is used correctly. By breaking down decision-making processes into manageable, meaningful steps and taking users’ preferences into account, AI creates a basis on which well-founded and accurate decisions can be made. This means that the choice of mentor is not left to chance, but is based on well thought-out, transparent criteria that ensure an optimal match. With AI as a supporting tool, the decision becomes a consciously designed process that takes full account of individual needs and goals.