Acting quickly to address concerns is admirable, but with the complexities of machine learning, ethics, and of their points of intersection, there are no quick fixes. To implement, scale, and maintain effective AI ethical risk mitigation strategies, companies should begin with a deep understanding of the problems they’re trying to solve. A challenge, however, is that conversations about AI ethics can feel nebulous. The first step, then, should consist of learning how to talk about it in concrete, actionable ways.
7
76 reads
CURATED FROM
IDEAS CURATED BY
The idea is part of this collection:
Learn more about technologyandthefuture with this collection
How to develop a growth mindset
How to think creatively and outside the box
How to embrace change
Related collections
Read & Learn
20x Faster
without
deepstash
with
deepstash
with
deepstash
Personalized microlearning
—
100+ Learning Journeys
—
Access to 200,000+ ideas
—
Access to the mobile app
—
Unlimited idea saving
—
—
Unlimited history
—
—
Unlimited listening to ideas
—
—
Downloading & offline access
—
—
Supercharge your mind with one idea per day
Enter your email and spend 1 minute every day to learn something new.
I agree to receive email updates