Twitter CEO Jack Dorsey was recently interviewed—via Twitter, naturally—by Recode’s Kara Swisher and was surprisingly candid about his company’s “huge fail.” Swisher pressed him on Twitter’s track record of “tech responsibility,” or the idea that, as a Silicon Valley leader, the company should be doing much more to address issues like diversity, harassment, and fake news.

Dorsey admitted that Twitter should be doing a better job, grading the company’s performance at a “C” (Swisher countered that it’s an “F” in her opinion). Dorsey’s honesty is refreshing, but he’s certainly not the only executive facing these struggles. While the nuances of them may differ, in today’s day and age, ensuring more ethical practices is a top concern for nearly every organization.

And given the pervasiveness of data access and analytics, instilling a better code of ethics for many companies starts with ensuring the responsible collection and use of information.

Take a look at this DataScience.com article, which outlines how various industry groups and stakeholders are grappling with this challenge.

The data science equivalent of the Hippocratic Oath is one such approach. This idea of establishing codes of conduct for data scientists and others working closely with data was explored at Bloomberg’s 2017 Data for Good Exchange, and the topic also featured prominently at last year’s event (check out this APEX post for more 2018 D4GX takeaways).

Another idea is to try to address ethical and legal concerns within the technology itself, by developing tools that enable the responsible collection, sharing, and analysis of data.

Yet another approach is to focus on workplace diversity with a specific concentration on the groups developing artificial intelligence (AI) technology and other advanced applications. The Wall Street Journal’s Sue Shellenbarger recently explored how numerous companies are trying to address biased algorithms by recruiting more women and minorities to work on their development teams. As she put it, “Artificial intelligence isn’t always intelligent enough at the office,” and hiring a more diverse workforce may help address inherent algorithmic bias and related concerns.  

Ensuring greater tech responsibility isn’t a task solely for the C-Suite. As individuals who both contribute to and benefit from the massive amounts of data generated on a daily basis, we all have a role to play in determining the ethical use of this information.

To quote the authors of the DataScience.com piece, “We should be having these conversations [about technology and ethics] not just at academic conferences and in tech and ethics courses, but around dinner tables, everywhere.”

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