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As is usual with disruptive technologies, the speed of AI development has quickly outpaced the speed of regulation.
A number of lawsuits have already been leveled against companies for either developing or simply using biased AI algorithms.
Unveiled earlier this month, the bill is likely to become law within the next few years.
Tech companies that fail to comply will risk Europe-wide class actions.
Its a set of recommendations that government agencies and technology companies may voluntarily comply with or not.
And its not just legal fees companies need to be concerned about.
Public trust in AI is waning.
68% didnt think so.
Businesses that take the steps to adopt ethical AI practices could reap the rewards.
So why are so many slow to take the plunge?
Before governance, people were moving straight from experiments to production in AI, says Krishnan.
Why is this happening?
They couldnt explain why the AI was making certain decisions.
Krishnan pointed out that this transparency also helps to break down knowledge silos within a company.
Those looking into the system wont know what happened.
Now people are producing manual documents for auditing purposes after the fact, she says.
Instead, starting to document now can help companies prepare for any upcoming regulations.
So wont taking the time for AI governance slow down this process and stifle innovation?
All of these are designed to make you go faster, safely.
Thats how I would think about AI governance.
No one wants faulty products and services.
Still not sure where to start?
This helps take the pressure off of data science teams, allowing them to focus on other tasks.
Before you buy a car, you want to try it out.
