This is the latest example of how bias creeps into artificial intelligence.
By Andrew Thompson | MOTHERBOARD
John Giannandrea, Google’s head of artificial intelligence, told a conference audience earlier this year that his main concern with AI isn’t deadly super-intelligent robots, but ones that discriminate. „The real safety question, if you want to call it that, is that if we give these systems biased data, they will be biased,“ he said.
His fears appear to have already crept into Google’s own products.
In July 2016, Google announced the public beta launch of a new machine learning application program interface (API), called the Cloud Natural Language API. It allows developers to incorporate Google’s deep learning models into their own applications. As the company said in its announcement of the API, it lets you „easily reveal the structure and meaning of your text in a variety of languages.“
In addition to entity recognition (deciphering what’s being talked about in a text) and syntax analysis (parsing the structure of that text), the API included a sentiment analyzer to allow programs to determine the degree to which sentences expressed a negative or positive sentiment, on a scale of -1 to 1. The problem is the API labels sentences about religious and ethnic minorities as negative—indicating it’s inherently biased. For example, it labels both being a Jew and being a homosexual as negative.
Google’s sentiment analyzer was not the first and isn’t the only one on the market. Sentiment analysis technology grew out of Stanford’s Natural Language Processing Group, which offers free, open source language processing tools for developers and academics. The technology has been incorporated into a host of machine learning suites, including Microsoft’s Azure and IBM’s Watson. But Google’s machine learning APIs, like its consumer-facing products, are arguably the most accessible on offer, due in part to their affordable price.