Intro
My initial research was reviewing the mentoring experience both from a mentor and mentee perspective, with the aim of redesigning the interaction via a gamified framework. This aim has developed from what I have perceived as a gap in the mentoring process indicated in my research, where those interviewed were looking for direction/ next steps in their different journeys but lacked the mechanism to facilitate this. The framework this project is looking to develop is not aiming to ascribe answers to mentees, but to help them in generating their own, with or without the support of a mentor.
Such being the case, during the last iterations of my research, it has transcended into deeper exploration of the self-mentoring* experience and how AI technology can enable and facilitate it.
Current research question
How can the mentoring experience be reimagined – enhanced and facilitated through AI technology?
- By providing and guiding users through a structured framework?
- By utilising existing data to provide a more beneficial journey?
- By harnessing similar data to inform decisions and gamify the experience?
Research Methodology
Semi-structured interviews
In order to test and further develop my hypothesis, I have chosen semi-structured interviews as a primary research method. Whilst testing the framework and due to the sensitivity of the questions, I am asking the interviewees to type / write down their answers and not disclose them before the end of the interview. Still, the majority of the respondents chose to voice out their answers. To establish trust and observe the natural behaviour of the interviewees (as much as possible over a video call), this methodology proved to be working. (see Appendix 1.0)
Research
Primary research
General findings
Confirmed hypothesis of a working framework: participants gained more clarity for their next steps / had an answer / direction on how to proceed to solve the issue in their area.
They needed more support when providing answers – more than 75% would prefer pre-defined answers to choose from, instead of them coming up with the answers. 50% would like to be able to complement pre-defined answers with their own.
Preferred method of answering the questions – speaking out loud (voice) or typing on computer.
Dreams
All participants found it hard to define what their “wildest dreams” in the particular area were. As expected, the more the area has been narrowed, the clearer the answers on their side were.
Fears
One thing I encountered was how open the participants were about talking about their fears. In most of the cases they were also very well identified. Participants found this step to be the easiest when answering the questions.
Strengths
All participants found it hard to identify their strengths, related to the particular area they were working on. After some initial guidance on my side (suggesting sample answers) they quickly picked up, still, I would assume due to humbleness and modesty, they did not recognise and reveal their full potential.
Challenges
Initial findings are showing respondents at this step are quite often defining “impossible to overcome” challenges. However with some slight guidance and discussion, they are transitioning into their own..
Answers and findings
Coming naturally, sometimes subconsciously → confirming the hypothesis the framework is functioning.
Secondary research
Bibliography
- Donald A. Norman – Emotional Design
- Edward de Bono – Six thinking hats
- Tom Kelley & David Kelley – Creative Confidence
- Phil Knight – Shoe dog
- Barry Schwartz – The paradox of choice
Sources/references for the near future:
- Henry Petrovski – Success through failure
- John Thackara – In the Bubble, Designing in a complex world
- Nir Eyal – Indistractable
- Nick Bolstrom – Superintelligence
- David D. Luxton – Artificial Intelligence in Behavioral and Mental Health Care
Publications
- The Invisible Teacher: A self-mentoring sustainability model by Dr Marsha Carr
Watson School of Education University of North Carolina Wilmington
- Understanding artificial intelligence ethics and safety
Alan Turing Institute
Research of Mental health apps approved by NHS – NHS website
Interventions
Framework creation
Based on previous primary and secondary research and self-reflection, I have set up the following framework, which served as the basis for my latest iteration:
Area of focus → Dreams → Fears → Strengths → Challenges → Answers
Testing data set
As a result of the interviews, I have gained some initial data, which can be utilised as a testing dataset to train a neural network.
Next interventions
→ ML model (dependant on gathering a larger and higher quality dataset)
→ Framework for frameworks: why limit to one framework, when a framework for frameworks can be developed? There is great potential in using Ai to guide both mentors and mentees to models and frameworks tailored to their specific needs. This is an area for further investigation.
Concluding
My research had led me on a journey, with initial findings influencing the more detailed areas of investigation. This has meant that I have had to be careful to avoid inbuilt bias within the research. In particular, consideration must be given to AI ethics, where both confidential and highly personal data must be treated with care to prevent bias in future recommendations and any other AI implementations (predictions, etc.). The knowledge that the current research is generating is not extensive enough yet to provide assurance of an AI mentorship experience applicable and suitable for all, due to the current small subset of people interviewed. However, expanding upon this with a higher volume of qualitative data will allow more reliance and certainty to be placed on the findings. Therefore, for the next phase of my research, I am looking to extend my interview program, targeting specific types of interview candidate based on the findings of current research, ensuring that initial key findings were not anomalies, but indicative of wider trends.
Appendix 1.0
→ Trust: There would have to be a relationship between the interviewer and the interviewee that transcended the research, that promoted a bond of friendship, a feeling of togetherness and joint pursuit of a common mission rising above personal egos.
→ Naturalness: As with observation one endeavours to be unobtrusive in order to witness events as they are, untainted by one’s presence and actions, so in interviews the aim is to secure what is in the mind of interviewees, uncoloured and unaffected by the interviewer.
Source: Adapted from Woods, 1986