Acing the algorithmic beat, journalism’s next frontier » Nieman Journalism Lab
▻http://www.niemanlab.org/2019/02/acing-the-algorithmic-beat-journalisms-next-frontier
Algorithms shape large parts of everyday life: our interactions with other people, what products we purchase, the information we see (or don’t see), our investment decisions and our career paths. And we trust their judgment: people are more likely to follow advice when they are being told that it came from an algorithm rather than a human, according to a Harvard Business School study.
Machines make mistakes
Despite our growing reliance on algorithms, the Pew Research Center found that Americans are concerned with the fairness and effectiveness of computer programs that make important decisions in their lives. 58 percent feel that algorithms are likely to reflect some level of human bias.
And they’re right. Even though algorithms can seem “objective” and can sometimes even outperform human judgment, they are still fallible. The notion that algorithms are neutral because math is involved is deeply flawed. After all, algorithms are based on data created by humans — and humans make mistakes and have biases. That’s why American mathematician Cathy O’Neil says: “Algorithms are opinions embedded in code.”
Machine bias can have grave consequences. A hiring algorithm at a large tech company might teach itself to prefer male applicants over female applicants. Policing software that conducts risk assessments might be biased against black people. And a content recommendation algorithm might amplify conspiracy theories.