From the course: Design Thinking in the Age of AI
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Keeping AI in check
From the course: Design Thinking in the Age of AI
Keeping AI in check
- As I've shared in this course, AI has the power to revolutionize design thinking, but as we have also heard in some of our favorite pop culture moments, with great power comes great responsibility. In our design thinking strategy and process, it's crucial to ensure our AI solutions are fair and don't lead to unintended negative consequences. One of the main ethical concerns with AI is bias. AI systems learn from data, and if the data's biased, the AI will likely reproduce and even amplify those biases. This can lead to unfair outcomes, particularly for marginalized groups. To tackle this, it's essential to use diverse and representative datasets, and continuously monitor AI outputs for signs of bias. Additionally, incorporating fairness checks and bias mitigation algorithms during the development phase can help in addressing these issues proactively. Transparency is another key factor. Users should understand how AI decisions are made. This can be achieved by implementing…
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