Data Matters Ethics, Data, and International Research Collaboration in a Changing World: Proceedings of a Workshop (2018) / Chapter Skim
Currently Skimming:
3 Emerging Technologies and the Social Landscape
3 Emerging Technologies and the Social Landscape
Pages 47-60
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 47... ...
The second session, on artificial intelligence, featured three presentations, by John Markoff, Research Fellow at the Center for Advanced Study in the Behavioral Sciences at Sanford University; Dario Gil, Chief Operating Officer of IBM Research and Vice President of AI and Quantum Computing at IBM; and Melvin Greer, Chief Data Scientist Americas at Intel Corporation. Following the presentations, Markoff moderated a discussion with his fellow panelists.
|
From page 48... ...
IBM's position on data responsibility, he explained, is that any organization that collects, stores, manages, or processes data is obliged to handle it responsibly, where responsibility entails issues regarding ownership, data flows access, security and trust, and the role of artificial intelligence. IBM's view is that its clients own their data and the insights derived from those data, and that the owners of data -- not governments -- should decide where data are stored and processed.
|
From page 49... ...
The third example involved service personalization based on personal data captured by electronic devices and other means. Tripathi noted that in India and the Middle East, advertising appears on mobile phones as people travel, something that people in the United States would likely revolt over.
|
From page 50... ...
Hospitals already have sensor data aggregated from patients who have had similar surgeries and good or bad postoperative recovery situations, but the issue is that data from an individual patient are covered by the Health Insurance Portability and Accountability Act, which made it difficult to get personal data from live postsurgical patients to test the system. In summary, Tripathi made three points that need to be considered when entering into a multinational, collaborative partnership involving data.
|
From page 51... ...
Work on artificial neural networks began in the 1940s, but the deep learning explosion, as Gil called it, occurred in 2012, when large labeled data sets merged with deep neural networks running on powerful graphical processing unit hardware accelerators to produce "the largest decrease in the error rate in history" when a computer system classified visual images. Within 3 years, in fact, deep neural networks had a lower error rate than humans at classifying visual images for specific domains.
|
From page 52... ...
Regarding the issue of bias, diversity, and inclusion, Gil recounted a recent incident where a researcher from the MIT Media Lab contacted IBM about a test she had run on artificial intelligence facial recognition systems developed by Microsoft, Face++ Cognitive Services, and IBM. Using photographs of parliamentarians from all over the world to test the accuracy of these services, she found that the error rate for females with dark complexions was between 23 and 36 percent for the three systems, compared to less than 1 percent for white males.
|
From page 53... ...
What he is seeing is that industry is forming its own ethics groups to guide the development of artificial intelligence and that companies are establishing their own ethics boards as a means of gaining the public's trust that it is developing artificial intelligence in an ethically responsible manner. "We will not get the benefits of artificial intelligence and all promise associated with it if people believe that it has all of the same biases, all of the same foibles, all the same ways of thinking that humans do today," said Greer.
|
From page 54... ...
At one end, John McCarthy coined the term artificial intelligence and claimed in a 1962 proposal to the Defense Advanced Research Project Agency that he would create a set of technologies that would ultimately replace the human being. On the other side of campus, Douglas Englebart invented the term intelligence augmentation to reflect the philosophy that this new form of computing would extend rather than replace humans.
|
From page 55... ...
Markoff asked if GDPR's Article 22, which states that "the data subject shall have the right not to be subject to a decision based solely on automated processing, including profiling, which produces legal effects concerning him or her or similarly affects him or her," had a chilling effect on the company's artificial intelligence work in Europe, and Gil replied that the European Union has issued a clarification that Article 22 was not meant to outlaw artificial intelligence. Gil said he thinks Article 22 has to do more with the explainability of algorithms.
|
From page 56... ...
One approach the company is taking is to create application-specific integrated circuits that are married to specific deep learning algorithms, providing a mechanism for tuning, verifying, and evaluating algorithms within a silicon architecture. Markoff then asked Gil and Greer to comment on whether fictional models of artificial intelligence -- such as HAL in the movie 2001: A Space Odyssey, or the sentient artificial intelligence program in the movie Her -- get in the way of a clear view of where this technology is headed.
|
From page 57... ...
Markoff then asked if there were technologies that could serve as an "antibot" to counter this type of attack, and Greer said Intel is developing artificial intelligence capabilities that can identify bias and deceit in artificial intelligence offerings. "We are deconstructing a cleansing, tagging, classification, and labeling model that would help us to figure out how data is being used and internalized to create a deceptive position or view," said Greer.
|
From page 58... ...
The next great advance in computational power, said Gil, will come with quantum computing, an entirely new paradigm that has enormous potential beyond artificial intelligence but that will have profound implications for how scientists model nature, assimilate chemistry, do optimizations, and perform machine learning. According to Gil, quantum computers are working already, though they are about where classical computing was in the 1950s.
|
From page 59... ...
Greer added, though, that if even one-tenth of 1 percent of jobs targeted by artificial intelligence were going to be affected in the first 10year timeframe, society should have a fundamental conversation about the future of work. In his mind, the most pressing problem today is not the future of work but dealing with the issues of trust and transparency.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.