Ethics (Artificial Intelligence) – Defending Our Privacy

Anil Kumar Kummari

Now a days All are accessible to use high end technology in mobile phones, for everything we are we are giving our information like fingerprint, Eye Scanner ( Retina Recognition ), health Apps will track your moments also. All our information is in the at one place. Once it hacked or miss used it will be at risk. As artificial intelligence proliferates, companies and governments are aggregating enormous data sets to feed their AI initiatives.

Although privacy is not a new concept in computing, the growth of aggregated data magnifies privacy challenges and leads to extreme ethical risks such as unintentionally building biased AI systems, among many others. Privacy and artificial intelligence are both complex topics. There are no easy or simple answers because solutions lie at the shifting and conflicted intersection of technology, commercial profit, public policy, and even individual and cultural attitudes. Data protection officials from more than 60 countries expressed their concerns over challenges posed by the emerging fields of robotics, artificial intelligence and machine learning due to the new tech's unpredictable outcomes. The global privacy regulators also discussed the difficulties of regulating encryption standards and how to balance law enforcement agency access to information with personal privacy rights.

Such technological developments “pose challenges for a consent model of data collection,” and may lead to an increase in data privacy risks, John Edwards, New Zealand privacy commissioner, said at the 38th International Data Protection and Privacy Commissioners' Conference, in Marrakesh, Morocco. For example, decision-making machines may be used to “engender or manipulate the trust of the user,” and would be an “all seeing, all remembering in-house guests,” that would collect personal data via numerous sensors. Peter Fleischer, global privacy counsel at Alphabet Inc.'s Google, said that established privacy principles would continue to be relevant for new technologies, but machine learning raised particular problems, such as machines finding “ways to re-identify data.”

The emerging technologies may have a broad impact across various industries. “Humans teaching machines to learn” was a “revolution in the making” that may have broad societal consequences that could cut across numerous economic sectors, Fleischer said. For example, data-driven machines may have the ability to analyse sensitive medical data, make medical diagnoses, thereby potentially revolutionizing the health-care industry, Fleischer said at the conference. Machines that learn would act “like a chef: see the ingredients and comes up with something new,” he said.

“Before the prospect of an intelligence explosion, we humans are like small children playing with a bomb. Such is the mismatch between the power of our plaything and the immaturity of our conduct.”

Nick Bostrom, Professor in AI Ethics and Philosophy at the University of Oxford

Google CEO Sundar Pichai thinks we are now living in an “artificial intelligence-first world.” He’s probably right. Artificial intelligence is all the rage in Silicon Valley these days, as technology companies race to build the first killer app that utilizes machine learning and image recognition. Today, Google announced an AI-powered assistant built into its new Pixel phones. But there’s a pivotal downside to the company’s latest creation: Because of the very nature of artificial intelligence, our data is less secure than ever before, and technology companies are now collecting even more personal information about each one of us.

Re-Defining Privacy

Unfortunately, the answer is no. We cannot turn back time. There is no completely private space available to us, anymore. Most of the things we do are already registered as data somewhere (and this occurs as soon as we do them). Purpose limitation is not always possible. We have fallen in love with the algorithmically driven companies that utilize technology to deliver an instantly better user experience. They pervade all aspects of everyday life. We already live in a world of big data. In addition, we cannot stop the emergence of artificial intelligence. The Internet of Things means that all of our devices are already connected (or will be connected in the near future). Connected and smart cities will continue to make our lives better. Our telephones already keep track of our moves and our connections and favourite places. Smart fridges keep track of our groceries. The list goes on and on. Moreover, perhaps most obviously, we love being connected and sharing our lives with others, via social media and other online platforms.

This does not mean that privacy disappears or that it ceases to matter.

Privacy is, and will continue to be, enormously important. Rather, privacy has been transformed by the proliferation of network technologies and the new forms of unmediated communication that such technologies facilitate.

In particular, technology has changed the character of the “zone” of privacy that people expect to be protected. There has been a shift from a settled space based on a clear distinction between public and private life to a more uncertain and dynamic zone that is constructed by and between individuals. Privacy as a well-defined space over which a person has “ownership” has been replaced by a more complex space that is constantly being negotiated and contested.

Work is similarly transformed. Businesses are becoming more flexible ecosystems / networks / platforms. “Lifetime” employment is no longer feasible or even desirable in a digital world. Working relationships become looser and more transitory as businesses are introducing more flexible work arrangements in which “employees” are “hired” for well-defined, but successive “tours of duty”.

Keeping artificial intelligence data in the shadows

One way for IT to address data privacy issues with machine learning is to "mask" the data collected, or anonymize it so that observers cannot learn specific information about a specific user. Some companies take a similar approach now with regulatory compliance, where blind enforcement policies use threat detection to determine if a device follows regulations but do not glean any identifying information.

“With AI it becomes easier to correlate data ... and remove privacy.”

Brian Katz

Device manufacturers have also sought to protect users in this way. For example, Apple iOS 10 added differential privacy, which recognises app and data usage patterns among groups of users while obscuring the identities of individuals. Tools such as encryption are also important for IT to maintain data privacy and security. Another best practice is to separate business and personal apps using technologies such as containerisation. Enterprise mobility management tools can be set up to look at only corporate apps but still be able to white list and blacklist any apps to prevent malware. That way, IT does not invade users' privacy on personal apps.

Reference:- 

1. https://gizmodo.com/googles-ai-plans-are-a-privacy-nightmare-1787413031
2. http://searchmobilecomputing.techtarget.com/news/450419686/Artificial-intelligence-data-privacy-issues-on-the-rise
3. https://medium.com/startup-grind/artificial-intelligence-is-taking-over-privacy-is-gone-d9eb131d6eca