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Its now clear that 2023 was the year ofartificial intelligence.
SinceChatGPTburst into the mainstream, weve seenAIspread into virtually every industry.
From an ethical-data standpoint, the mainstreaming of AI brings obvious challenges.
Who decides which data is fed into AI tools, and for what purpose?
How should data persist in algorithms, and what does that mean for consent andprivacy?
What kinds of guardrails are needed to keep us safe in a world of omnipresent AI?
These are important questions.
Head of Solutions at Ketch.
As a result, regulators are learning to regulate purposes and outcomes instead of specific technologies.
The push to create more flexible rulebooks mirrors the way that businesses are evolving toward more adaptable data solutions.
Its clear, for instance, that algorithmic bias is real.
Building out organization-wide data mapping and rigorous consent management is thus a vital piece of the ethical AI puzzle.
Going a step further, solving for bias requires advanced data-privacy capabilities.
But putting such methods into action is only possible if privacy practitioners step up.
The trouble is, that commitment cant only extend to responsible AI innovation.
The stakes are high, and the opportunity is real.
We’ve featured the best data visualization tool.
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