Marian Croak, one of Google’s few Black executives, has been appointed to supervise responsible research on Artificial Intelligence (AI). This comes after weeks of unrest over the firing of a prominent Black scientist- Timnit Gebru. Timnit Gebru was the Ethical AI co-lead and she claimed to have been fired abruptly for contesting company orders. This led to an internal kerfuffle between staff and management, with staff expressing concern that Gebru’s critiques of Google was met with unfair consequences. Marian Croak happens to be part of the executives acting as mediator between the employees and the management, trying to broker a way forward. In a Thursday meeting with employees, Croak mentioned that she respected Timnit Gebru and that she considered what happened to her as rather unfortunate. She expressed disagreement in the fields of research now under her management, stating in a video on Google’s blog that: “There’s quite a lot of conflict right now within the field, and it can be polarizing at times, and what I’d like to do is just have people have the conversation in a more diplomatic way.”
Alex Hanna, a Google employee, via Twitter deemed Croak’s appointment as ‘a betrayal’, claiming that it did not see to the demands of the Ethical Artificial Intelligence team, and that it happened behind their back. Gebru, who seems to be the victim, expressed similar feelings. In a statement she said: “Marian is a highly accomplished trailblazing scientist that I had admired and even confided in. It’s incredibly hurtful to see her legitimizing what Jeff Dean and his subordinates have done to me and my team.”
Alphabet Inc’s Google confirmed that Marian croak, as the new overseer, will be in charge of ten teams, including a dozen of scientists studying the ethical considerations of automated technologies of Artificial Intelligence. Marian Croak who is also a Vice President of Engineering at Google, will report to Google Artificial Intelligence Chief Jeff Dean. Croak, will also manage teams carrying out research related to accessibility, social good and fairness in health algorithms.