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What are the consequences of that disadvantage and what can we do about it? Are we collecting enough data so that we can make accurate decisions about everyone the AI ​​affects? If you want to make decisions bas on unfair criteria, such as ethnic origin, gender, geography or income, you ne fairness through consciousness . So you have to collect sensitive variables to see the correlation between data, but not to make decisions bas on those sensitive variables or their proxies. As we discuss in the loan example, proxy variables affect your model, so we ne to address that as well. At Salesforce, for example, we found out early on that the name ‘John’ was the most important prictor of a good sales lead in lead scoring.

They Can Provide Despite

First name” is a proxy for gender and can be a proxy for ethnic origin or country of origin. As a result, the team remov ‘name’ as one of the variables in the model. 3. Put yourself in the shoes of the people the technology may affect Since none of us can fully understand someone else’s reality, AI developers should seek direct feback from Romania Phone Number List customers. This way they can find out how their technology affects a certain group of people. For example, at Salesforce, our Research and Insights teams host User Summits. Employees and consumers then come together to gain a good insight into the context, nes and concerns of both groups regarding data collection and personalization, among other things.

Not Being in the Store

This allows us to develop features and guidelines for our products that everyone involv can trust. 4. Don’t fall back on the motto ‘move fast and break things’ Honesty is a complex concept that requires quite a bit of effort. Especially DV Leads when AI impacts human rights (justice, privacy, health, access to food, or housing), you are even more responsible for an accurate, fair decision. While the industry has collectively mov away from the “move fast and break things” mentality in recent years, there is a chance that we will take a step back due to COVID-19. Organizations try to react quickly to adapt.