Karen Hao Empowers Journalists To Unravel AI’s Complexities And Impacts

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Karen Hao Empowers Journalists To Unravel AI’s Complexities And Impacts
ReportingArtificial IntelligenceTraining
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Hessie Jones is an Author, Strategist, Investor and Data Privacy Practitioner, advocating for human-centred AI, education and the ethical distribution of AI in this era of transformation.

Use Generative AI To Boost Your Stonewalling Skills So You Don’t Have To Resign, Get Fired, Or Be In The DoghouseI awoke at the early hours of 4:00 am EDT to attend the first, in the series of online courses for Artificial Intelligence is Creating a New Colonial World Order.

Second, there's the issue of separating fact from fiction, hype from reality. As Hao points out,"AI is sort of this big tent term that refers to all of these many different technologies. And Marvin Minsky, another founding father of AI... calls AI a suitcase word. So, you can shove whatever meaning you want into the suitcase and suddenly it becomes AI.

This 360-degree view is aimed to help journalists understand the technology's capabilities and limitations and enable them to engage in stories with more critical thought to cut through the hype and ask the right questions. Finally, Hao emphasizes the importance of remembering the human element in AI stories, stating,"It would be a shame to forget that the story is about people." Behind every AI development or application, there are people affected, so focus on how AI systems impact individuals, communities, and society at large, rather than just discussing the technology in abstract terms. Also, consider the human developers, designers, and decision-makers.

At this juncture of AI advancement, the development of AI systems means we also need to question the motives. As Hao points out,"The dominant vision of AI has really shifted from rule-based systems to increasingly big data and big compute-based systems... it really comes down to who is developing and who is funding AI."To dig deeper into AI stories journalists should ask probing questions at each stage of the AI development pipeline.

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