Reading the news in the last few weeks, there are several recurrent themes that stand out: the increasing loss of privacy for social media users and consumers; the widespread emergence of artificial intelligence and machine learning across nearly all private and public sectors, and what the Economist calls the “techlash” of individuals protesting at the intrusions into their privacy, and to take it a step further, the pervading dread that AI is going to take their jobs – as well as distrust of the internet and social media platforms.
In response, about half of respondents to a Pew Research Center study say they are abandoning or limiting social media use.
Companies have been collecting, selling, and reusing personal data for decades, but now that Americans are finally concerned, it may be too late. According to Pew, 91 percent of Americans feel they’ve lost control of how their personal data is collected and used. Some are resigned to the tradeoff between privacy and online convenience; others are advocating for companies to adopt more stringent privacy policies.
In another study by Journalism.com, of the two-thirds of Americans, who have heard of social media bots, “many are concerned that bots are used maliciously and negatively affect how well-informed Americans are about current events.”
It’s a fitting response to the erosion of tech trustworthiness and requires a comprehensive discussion by consumers, policymakers, the big tech companies, and many other experts including academia, and legal and cybersecurity professionals.
Be an Informed, Cyber-secure Internet User
October is National Cybersecurity Awareness Month – a great time to review your online privacy profile, social media use and internet browsing practices. Visit https://staysafeonline.org/ncsam for advice and step-by-step instructions for how to safeguard your online identity, recognize fake URLs, and secure your mobile telephone.
There are privacy and cybersecurity dimensions to AI and machine learning centered in how they make use of big data.
Machine learning is a method of data analysis that, through the use of algorithms, automates analytical model building. It is a form of AI based on the premise that systems can apply “knowledge” from large data sets and “learn” to identify patterns for use in facial recognition, speech recognition, object recognition, language translation, and many other uses.
Major tech and retail companies built scalable big data structures and applications then made their data accessible. By opening access to these big data structures, they allowed data to be used as a commodity driving business solutions, spawning new industries, jobs, prosperity and creativity.
Tech companies and other organizations are using AI to boost network security and supply chain management. AI helps automate complex processes for detecting attacks and responding to breaches. These applications are becoming more and more sophisticated as more advanced algorithms are developed.
Automated tools can detect, analyze and defend against advanced attacks by detecting attackers. Likewise, AI can also expose vulnerabilities, particularly when it interfaces within and across organizations that unintentionally allow access by scammers – and worse. Attackers are leveraging AI by developing automated attack scenarios that study and learn about systems to identify their vulnerabilities.
Just as the internet forever transformed American life, AI and machine learning are disrupting and revolutionizing every sector of American life today. Some foresee a dystopia of robots becoming the dominant form of intelligence on Earth; others have a more sanguine view.
In fact, technology advances from the beginning of time have had a disruptive impact on societies and workers – from the invention of the wheel to the self-driving vehicles of today – everyday life changes. Old jobs disappear and new jobs are created.
A report from the World Economic Forum predicts that machines will perform more than half of all “work tasks” by 2025, compared to just 29 percent today, which will lead to the displacement of 75 million jobs between now and 2022. At the same time, over the same five-year period, a projected 133 million new jobs will be created, leading to an actual increase of 58 million more new jobs.
In this edition, in an interview with Dr. Mary "Missy" Cummings, a professor in the Duke University Pratt School of Engineering and director of the Humans and Autonomy Laboratory, Cummings argues that while tedious, dangerous jobs will be lost, in the long-term, displaced workers will perform better-paying high tech jobs that will lead to greater job satisfaction. Freed from repetitive, hazardous tasks, the workforce of the future will be better positioned to exercise their critical thinking and creative skills.
Cummings and other robotics experts say the key will be reskilling and upskilling the workforce to fill the highly technical jobs of the future.
To be prepared, the National Institute of Standards and Technology (NIST) National Initiative for Cybersecurity Education (NICE) can show you the rewards of choosing a career in cybersecurity and IT and how to close your skills gap. Interested in a new career now – there is a critical nationwide shortage of IT/cyber workers today across all sectors of business and government.
The departments of Defense and the Navy are pursuing pilots in AI and machine learning to ensure national and economic security. Deputy Secretary of Defense Patrick M. Shanahan directed the DoD Chief Information Officer to stand-up the Joint Artificial Intelligence Center (JAIC) to empower teams across the department to rapidly deliver new AI-enabled capabilities and experiment with new operating concepts in support of DoD's military missions and business reform efforts.
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Sharon Anderson is the CHIPS senior editor. She can be reached at firstname.lastname@example.org. .