More to Learn
About Machine Learning

In their Viewpoint “Learning Machine Learning” (Dec. 2018), Ted G. Lewis and Peter J. Denning used a Q&A format to address machine learning and neural nets but, in my view, omitted two fundamental and important questions. The first is:

Q. Is machine learning the best way to get the most reliable and efficient solution to a problem?

A. Not generally.

To explain my answer, I need a definition of “machine learning.” Machine learning is a machine collecting data while providing service and using the data to improve the speed or accuracy of the service. This is neither new nor unusual. For example, a search program can reorder its search list to move the most frequently requested items toward the top of the list. This improves performance until there is a major change in the probability of the items being requested. When this happens, performance may degrade until the machine “learns” the new probabilities. Suggestions offered by a search engine are also based on data collected while serving users; the search engine uses the data to “learn” what users are likely to ask.

When machine learning is used to “discover” an algorithm, it may find a local optimum, or an algorithm that is better than similar algorithms but very different from a much better one. A human who took the time to understand the situation might find that algorithm. Machine learning is often a lazy programmer’s way to solve a problem. Using machine learning may save the programmer time but fail to find the best solution. Further, the trained network may fail unexpectedly when it encounters data radically different from its training set.

The second Q&A pair Lewis and Denning should have addressed concerns “neural networks”:

Q. If developers have constructed (or simulated) a physical neural net-

A S I READ the specialsection on the China Region (Nov. 2018), I thought privacy in China deserved bet- ter treatment than was expressed in the section’s foreword “Welcome to the China Region Special Section” by co-organizers Wenguang Chen and Xiang-Yang Li, that “People in China seem less sensitive about privacy.” It sounded almost identical to what Robin Li, CEO and co-founder of Baidu, said in a talk at the March 2018 China Development Forum that was not well received by China’s Internet users. 2

A March 2018 survey of 100,000 Chinese households by CCTV and Ten-cent Research reported 76.3% of participants view AI as a threat to privacy. 1 Other global privacy surveys, including one by KPMG, reported privacy awareness in China as far more prevalent than the authors seemed to imply.

One of the few critical notes in the special section came near the end of the Elliott Zaagman’s article “China’s Computing Ambitions” when it called the lack of (Western-style) legal protections and transparency “a real concern.” This was followed by a quote on the weaknesses of more-open digital societies. When lack of privacy rights was mentioned elsewhere in the special section, it was described as “an accepted observation.” Feng Chucheng of risk-analysis firm Blackpeak, said, “Rather than simply reflecting [the status quo] that privacy protections are not well-developed in this society, [Baidu] should be leading the charge to improve privacy rights.” 2 Perhaps the professors and analysts who contributed articles to the section should have tried to do the same. It would not have detracted from the quality of their articles.

The “West” itself shows signs of mov-
ing toward being a surveillance society,
and no amount of “privacy rights” will
change that historical direction. More
than a few Western governments are
actually envious of China’s unique ap-
plications of technology in society. We
should be suspicious of government
agencies and regulators redefining pri-
vacy or downgrading it or citing nation-
al security to make such applications fit
their agenda. A similar observation can
be made about privately run corpora-
tions as well, especially social networks.

Articles and columns in Communications should include, along with technological achievement, considerations on how they might be abused and the lessons that should be learned when they are. It would mean extra work for every author, as well as increased reader skepticism, but would surely increase awareness.

As a New Year’s resolution, I respectfully invite everyone to read or reread the ACM Code of Ethics and Professional Conduct ( https://www.acm. org/code-of-ethics), especially sections 1. 1, 1. 2, and 1.6, and incorporate it into their research and professional practice, especially those with authority and influence—or who publish in its leading publication.

References

1. Hersey, F. Almost 80% of Chinese concerned about AI threat to privacy, 32% already feel a threat to their work. TechNode (Mar. 2, 2018); https://technode. com/2018/03/02/almost-80-chinese-concerned-ai- threat-privacy-32-already-feel-threat-work/

2. Li, R. Are Chinese people ‘less sensitive’ about privacy? Sixth Tone (Mar. 27, 2018); http://www. sixthtone.com/news/1001996/are-chinese-people- less-sensitive-about-privacy%3F

Vincent Van Den Berghe, Leuven, Belgium

Response from the Editor-in-Chief Van Den Berghe’s letter raises a good point—that articles discussing technology can and should be enriched by discussion of their societal context, including potential abuses. I am pleased to see this topic being raised in the context of the China Region special section and believe it applies much more broadly, both globally and across a variety of topics. This is an important challenge to Communications authors. I am sure they will rise to it.