Last Week in AI Bias in Voice Recognition, Debates in AI, and Robotics in the Time of COVID-19
Apr 4, 2020
Dive into the pressing issue of bias in voice recognition systems, which tend to disadvantage minorities due to limited training data. Delve into the debate on AI’s future and explore the impact of COVID-19 on robotics. Hear about the risks of deepfake technology and the need for better detection methods. Discover how misconceptions about AI's threat to jobs are challenged by the reality of automation in essential sectors. Uncover the transformative potential of robotics in healthcare and the call for innovative collaboration.
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Racial Bias in Speech Recognition
- Speech recognition systems show racial bias, making more errors with Black users than white users.
- This bias stems from training data that underrepresents Black individuals, creating a feedback loop.
Deepfakes and Media Integrity
- Deepfakes erode trust in media, necessitating detection solutions.
- However, detection alone is insufficient; it must be combined with journalistic fact-checking techniques.
Democratization of Deepfakes
- The main difference between current deepfakes and past techniques is increased accessibility, not necessarily increased sophistication.
- This democratization enables more malicious uses.
