Aliya Shaikhina's Profile

Ana, thank you so much for sharing this personal life example. Glad you support the development of tools for resolving it as much as I do, having lived in multicultural environments since a very young age. Tolerance and understanding for fostering strong inter-ethnical social connections comes from awareness about every bit of subtlety of these differences. The developments in AI make me cautiously optimistic about the tools for this to be there for us to use in our daily lives.

In fact, you just made me realize there is definitely an interesting use case, making these tools helpful not just organizationally but also, having affordable B2C solutions developed. It will take some time and research, technology, resources (including, data resources!) for it to happen but the future is near.

Shekeyla, thank you very much for your note and the tie to the QC case discussion. The reading for it and that discussion is what inspired me to explore this topic further. By the way, I appreciated your comment to Quantified Communications and opening up about being concerned of the ‘biased comparison’ of its AI algorithm. Thank you for not being afraid of being vulnerable. You surfaced an important concern.

I absolutely agree with your prediction there with potentially a range of groups from various fields working on it. It might be a good thing with competition driving the innovation. As long as there is demand for cracking the ‘culture code’ and creating sustainable business models around it to continue the updates.

Bert and Cem, thank you for covering an fascinating topic. I appreciate your evaluation of the possible ways to counter potential flaws of this tool.

My first reaction to this risk assessment tool was a little mixed. First of all, it immediately brought to mind anecdotal evidence of recidivist “being back at it” and causing harm again that frustrates the society. It makes any tool that would help strengthen the judges ability to make the “right” decision is appealing and seems justified (given they use it as a supplement along with the ‘checklist’ you described). On the other hand, the mindset shift I experienced watching the most recent cases of Archie Williams or Robert DuBois is truly terrifying, especially with racial biases that you mentioned. Either way, it is a high stakes decision with no margin for error. Biases is a very sensitive and current topic.

DNA tests really transformed the justice system. Largely thanks to the trust in the science behind it. I found this statistics fascinating https://innocenceproject.org/dna-exonerations-in-the-united-states/ I wonder if one of the ways Compas could build trust and strengthen its position is exploring areas for including risk assessment of wrongful convictions as well https://www.washingtonpost.com/crime-law/2020/09/16/more-than-half-all-wrongful-criminal-convictions-caused-by-government-misconduct-study-finds/ The type of data https://nij.ojp.gov/topics/articles/predicting-and-preventing-wrongful-convictions is not a lot to come by but could be interesting for them to explore.

A judge equipped with a set of tools, checklists and regulations for data analytics could also, be equipped with the balanced score of potential risk of their erroneous decision for convictions in the first place. Maybe it will help – behavioral economists suggest balancing the hope of the “benefits of change” with the fear of the “cost of no change”. Not for an individual case as we cannot connect them but on a systemic level.

Tyuchi, thank you very much for your excellent observation and comment. I absolutely agree that having algorithms “fed” with that ‘diversified’ data would significantly improve its ability to withstand the biases and errors within homogenous teams. Just like the decision to diversify teams, the motivation to focus on expanding its scope remains within the leaders’ decision-making realm. While it is easy to justify team diversity for “productive conflict” effect as well as to a greater range of talent and “world-views”, it might be harder to consistently motivate them to include these data into analytical dimension. For example, racial bias awareness is such a zeitgeist of the moment but will it always be…

Another concern I have is with data becoming more convoluted, cleaning it up from the analytics standpoint would be hassle-some and therefore, priorities might be drawn away from exploring cultural differences. Leaving it only to a few large transnationals to explore. Again, thank you for engaging in this discussion with me and your excellent point!

Ana, thank you for pulling all the resources we covered and making an interesting note about them “democratizing coaching” and making it accessible to all. I think your coaching services would still be needed 🙂 because of the “The Knowing-Doing Gap” research that you mentioned here as well as the quote from it goes individuals and organizations “know WHAT to do, know HOW to do it but DON’T do it”. This is where despite availability of these tools, an external accountability and motivating factors to get to know yourself as a leader are important.

I also, think you raise an important point here about these tools helping our identity as leaders. What I keep hearing at Harvard leadership courses is how, time and again, leaders place huge importance on being able to turn to their core values in the critical moments for the organizations they lead, whether it’s a pivot of a start-up or a transformation of a large corporation. They keep suggesting to ask yourself what you stand for, to define your leadership philosophy, and thereby, influencing their vision and building organization’s cultures and strategy. Identity is an important tool to build confidence for personal resilience during tough and trying times and decision-making for anyone but particularly important for leaders, whose identity has a ripple effect on the stakeholders, under their direct and indirect influence.

PS: I am not a tech person but would love to help you brainstorm your potential dashboard venture!

Thank you for covering the topic, Kaz! I agree with the considerations you had for an implementation of Sentiment Analysis. I believe the aspect of a “buy-in” from the employees is not quite covered in the article and in essence, it is purely focused on the benefits for the organizations at large, while they are targeting employees.

One research-based argument to potentially strengthen the usage of this analytical tool is the Harvard experiment we discussed in class on “The Hawthorne Effect” that refers to a type of reactivity in which individuals modify an aspect of their behavior in response to their awareness of being observed.

Following the discussion of this effect, there was a suggestion from Professor Polzer that particularly stuck in my mind about people potentially being motivated to improve performance was because “they felt seen”. It would be an interesting assumption to explore. If there is a narrative that companies can create from this perspective, people would be more willing to cooperate and that, in of itself could positively reflect on employee motivation and engagement.