Georges Badawi

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On April 11, 2020, Georges Badawi commented on Locked in by Algorithms? :

Very interesting article Paula. I kept going back and forth while reading it, tough to deice which side I fall on.

On one hand, i see the benefits of using algorithms to make the system more fair and equitable. However, the reliance on historical data is indeed a big drawback. While not an expert myself, the historical unfairness of the american judicial system, in particular on issues of race, have been hotly discussed lately. There are multiple articles, documentaries and movies on the topic. The data in this article even supports it. Therefore, the reliance on historical data to develop trends carries significant drawbacks that we don’t want to perpetuate.

Additionally, the point about education is incredibly important. Introducing analytics to the judicial system, an old and slightly archaic branch of government usually denominated by older professionals, will have a hard time finding strong footing. but this does not only apply to judges. it extends to the general public, majority of whom have to serve jury duty in case the claim goes to court.
Explaining to all these stakeholders what the code does and how to and not-to interpret will not be easy.

Considering all the above, I dont think they system is ready for such a change, at least not in the format and structure it is currently being offered.

On April 11, 2020, Georges Badawi commented on AI in Predicting Candidate Potential :

Very interesting article, and in a way very related to our blg post about using predictive analysis and algorithms to scout talent for soccer clubs.

A couple of thoughts. First, i completely agree that these platforms and systems should act more as compliments rather than substitutes for human based recruitment. I think that together, both can capture both types of patterns identified above.

Additionally, i keep thinking whether this discussion would be different based on the level of employees or job functions corporations are recruiting for. Thinking back on our Promo exercise, it was evident that we cant rely solely on data to select the next VP or high ranking executive. However, would data work perfectly to sort through hundreds of applicants for an order fulfillment job or grocery store cashier? Not that these jobs are in any way less important than others, particularly true in these current days, but the technical and soft skills required are less demanding.

On April 11, 2020, Georges Badawi commented on Nudging your way to the top? :

This is a very interesting article and concept. I was aware of nudging as a way to promote employee engagement and morale, but had no clue that there were official software making them possible.
While I think it is a great idea in general, there are 2 issues I foresee that make think twice about implementing such a system.

First, i believe there is a genuine concern that companies might overindex on ‘nudging’ and use it as a way to get their employees to perform tasks outside of their purview. While you did mention that one of the critical components for this to work is mutual benefit to both parties, this should really be highlighted as a potential issue. I can easily see big corporations with a large employee base nudging their staff to go the extra mile for customers. An example might be Walmart sending a grocery store clerk the right emails and messages from their managers to uplift his/her and then asking him/her to also help load out inventory in the deliveries bay, a task usually performed by a dedicated employee.

Another more general concern relates to data. We have seen in the course so far at least 4 different ventures that rely on collecting and analyzing employee data, interactions and communications to increase efficiency. However, each of these ventures targets a very different aspect of employee engagement and efficiency. At what point will employees say that there is too much going on and start pushing back at all these AI’s, software, algorithms and platforms.