- “LinkedIn today released the LinkedIn Fairness Toolkit (LiFT), an open source software library designed to enable the measurement of fairness in AI and machine learning workflows.
- ‘News headlines and academic research have emphasized that widespread societal injustice based on human biases can be reflected both in the data that is used to train AI models and the models themselves. Research has also shown that models affected by these societal biases can ultimately serve to reinforce those biases and perpetuate discrimination against certain groups,’”
“Mullainathan, who teaches a course on artificial intelligence at Booth, led a workshop at Management Conference 2019 that provided a functional understanding of A.I. Below are four of the top insights he shared.
- We can’t rely on our intuition to build algorithms.
- Instead of intuition, base algorithms on data.
- Algorithms aren’t biased, but they can mimic our biases.
- A.I. is best used for things we can’t do.”
- “Most consumers (58%) are more likely to recommend a company that can demonstrate its AI algorithms are bias-free, and more likely to purchase products or services from such businesses (56%). Gen Z (69%) and millennial (70%) respondents champion unbiased brands even more so.
- Only about a third (35%) of senior executives say their companies offer AI-related reskilling opportunities, no improvement from 2018.
- The top benefits of AI according to senior executives are improving customer experience and service (39%), the ability to leverage data and analytics (36%), and freeing up more time for employees to focus on more important tasks (35%).”