AI beat human in Stanford reading test, NLP breakthrough?

Credit: Jack Ma, CEO of the Alibaba Group (Koki Nagahama/Getty Images)

The ability to read is truly a huge evolutionary advantage for humanity. With written language we can retain and retract knowledge, passing it down for generations. The ability to write and read is the heart of human development over the last millennium. The AI industry has long sought to develop machines that possess this ability. In a recent article, Alibaba's AI Outguns Humans in Reading Test, Alibaba and Microsoft’s AIs have made significant progress in machine reading, beating the human average score in the Stanford reading test. This test based on more than 500 Wikipedia articles, and designed to figure out if AIs can process through a large quantity of data to answer the questions set. Both AIs, for the first time in history, score a higher score than human average. This mark a big step in Natural Language Processing development. According to this article, Microsoft acquired Maluuba, a company that uses deep learning to develop natural-language understanding, around this time last year, and has since then placed focus on making literate AIs. It’s amazing how in the article, which written last May, the co-founder of Maluuba still only hope to make the literate machine, and now they have developed AI that can surpass the average human score in a reading test. For Alibaba, they already apply this technology on Singles Day, the world's biggest shopping bonanza, by using computers to answer a large number of customer service questions, according to this article. It’s clear that research in literate AIs are growing quickly, and will soon be able to provide us much benefit.

Scoring higher than human on a test does not prove AIs reach a human reading comprehension level, however. We as humans can detect nuances, hidden message, sarcasm, etc. in reading, but these AIs still very impressive in their own right. The AIs clearly open many possibilities, including processing a large amount of data and making sense of it. Customer service, healthcare, virtual assistant, search engine, etc. all will benefit from this. If we keep this development rate, I think we can create AIs that hold all humanity digital knowledge and can answer any question with precise accuracy in the next 50 years. However, this technology also has flip side. Now AIs could potentially understand human communications, malicious AIs could potentially spy on a large scale, and make it easier to obtain valuable information without us noticing. Also, in development of new know-it-all AIs, if we not careful with the data we feed the AIs, the AIs knowledge could potentially get manipulate, just like how the Microsoft's twitter AI Tay eventually got shut down due to her access to uncleaned data.

This breakthrough is clearly related to our class Nature Language Processing topic at the beginning of the term. In class, we learned how machines can try to understand and process written language by parsing and using sentinel score. We also talk about how the technology available still cannot completely let machine understand language well because of the ambiguity of language. However, it seems like we are coming nearer and nearer to that goal. Of course, Alibaba and Microsoft’s AIs are using deep learning and not simple code we use in our politician analysis assignment, but we can hope that this technology will soon be accessible to the public. What a great time to be learning about AIs, when we can see the technology evolve day by day.

I’m excited to see new technology like this helping people in their life. However, I also concern about how this could affect our job market, as now AIs could potentially continue to replace human in the workspace. I'm also wondering if after making AIs that could inherit our current knowledge, could we start making AIs that create new knowledge, and should we do such thing?