The growth of low-end hardware has led to a proliferation of machine learning-based services in edge applications. These applications gather contextual information about users and provide some services, such as personalized offers, through a machine learning (ML) model. A growing practice has been to deploy such ML models on the user's device to reduce latency, maintain user privacy, and minimize continuous reliance on a centralized source. However, deploying ML models on the user's edge device can leak proprietary information about the service provider. In this work, we investigate on-device ML models that are used to provide mobile services and demonstrate how simple attacks can leak proprietary information of the service provider. We show that different adversaries can easily exploit such models to maximize their profit and accomplish content theft. Motivated by the need to thwart such attacks, we present an end-to-end framework, SODA, for deploying and serving on edge devices while defending against adversarial usage. Our results demonstrate that SODA can detect adversarial usage with 89% accuracy in less than 50 queries with minimal impact on service performance, latency, and storage.

Dr. David Bray is the Inaugural Director of the new global GeoTech Center & Commission of the Atlantic Council, a nonprofit for international political, business, and intellectual leaders founded in 1961. Headquartered in Washington, DC, the Council offers programs related to international security and global economic prosperity. In previous leadership roles, Bray led the technology aspects of the Centers for Disease Control's bioterrorism preparedness program in response to 9/11, the outbreak response to the West Nile virus, SARS, monkey pox and other emergencies. He also spent time on the ground in Afghanistan in 2009 as a senior advisor to both military and humanitarian assistance efforts, serving as the non-partisan Executive Director for a bipartisan National Commission on R&D, and providing leadership as a non-partisan federal agency Senior Executive focused on digital modernization. He also is a Young Global Leader for 2017-2021 of the World Economic Forum. Bray is a member of multiple Boards of Directors and has worked with the U.S. Special Operations Command on counter-misinformation efforts. He was invited to give the 2019 UN Charter Keynote on the future of AI & IoT governance. His academic background includes a PhD from Emory University; he also has held affiliations with MIT, Harvard, and the University of Oxford. He recently took a few moments to speak to AI Trends Editor John P. Desmond about current events, including the geopolitics of the COVID-19 pandemic. AI Trends: Thank you David for talking to AI Trends today.

On Wednesday night, Tesla sued four former employees and the self-driving startup Zoox for misappropriation of trade secrets. No, you're not having driverless-car lawsuit déjà vu--you're just remembering the time last year when Waymo and Uber settled their own trade secrets case after four days of trial. Tesla's suit, filed in the Northern California federal district court, alleges that four of its former employees took proprietary information related to "warehousing, logistics, and inventory control operations" when they left the electric automaker, and later, while working for Zoox, used that proprietary information to improve its technology and operations. Tesla says the former employees--Scott Turner, Sydney Cooper, Chrisian Dement, and Craig Emigh--worked in product distribution and warehouse supervising. It alleges they forwarded the trade secrets to their own personal email accounts, or the accounts of other former Tesla employees.

The last decade has seen a dramatic increase in our daily use of artificial intelligence. Nowadays, AI systems are being used in leading newsrooms around the world. I recently detailed AI's current roles in journalism, and the new possibilities they present. With these new possibilities come questions regarding ethical use of AI in newsrooms and the factors that should be considered when judging the moral application of AI in today's news. Here, we're going to examine the emerging ethics surrounding AI use in journalism as media professionals face new challenges never before met in the modern newsroom.

Five days into an epic court battle that was expected to last for weeks, Uber abruptly settled a lawsuit Friday brought by Waymo, part of Google parent Alphabet, over the alleged theft of trade secrets. As part of the deal, company officials said, Uber has agreed to pay 0.34 percent of the company's equity at a $72 billion valuation -- a sum that exceeds $244 million. The deal also includes a guarantee that Uber will not incorporate confidential Waymo self-driving-car technology into Uber's hardware and software, a Waymo spokesman said. The deal was announced in a San Francisco federal court before testimony began, shocking many in the audience and leading to a rapid succession of prepared statements from each side. Uber chief executive Dara Khosrowshahi released a statement saying he wants to "express regret" and commit Uber to taking steps to ensure that its self-driving technology "represents just our good work."

The end of a politician's time in office often inspires a turn toward the existential, but few causes are as quixotic as the one chosen by James Vacca, who this month hits his three-term limit as a New York City Council member, representing the East Bronx. Vacca's nearly four decades in local government could well be defined by a bill that he introduced in August, and that passed last Monday by a unanimous vote. Once signed into law by Mayor Bill de Blasio, the legislation will establish a task force to examine the city's "automated decision systems"--the computerized algorithms that guide the allocation of everything from police officers and firehouses to public housing and food stamps--with an eye toward making them fairer and more open to scrutiny. In mid-October, I and some of my colleagues from a group at Cornell Tech that works on algorithmic accountability attended a hearing of the Council's technology committee to offer testimony on the bill. As Vacca, who chairs the committee, declared at the time, "If we're going to be governed by machines and algorithms and data, well, they better be transparent."

On the face of it, Uber has had a terrible week in its legal brawl with Waymo, Google parent company Alphabet's self-driving car effort. First it suffered the public reveal of a long-awaited report that appeared to confirm Uber knew its former superstar engineer, Anthony Levandowski, took intellectual property from Google, his former employer, before it hired him. Then, over Uber's protest, the judge pushed the trial date back from this month to December, giving Waymo more time to prepare its case. To quickly sum up the case: Waymo alleges that when former star engineer Levandowski left the company in January 2016, he made off with thousands of documents containing its proprietary information, then used that intellectual property to jumpstart his own company, Otto. Uber acquired Otto for a reported $680 million in August 2016, and Waymo says Levandowski brought this stolen info with him--and that its intellectual property ended up in Uber's self-driving cars.

Two million years ago, when the first homo erectus shared his newfound discovery with his hominid peers, they likely ran for the hills. But once they realized everything they could achieve with fire--from seeing in the dark and keeping warm to cooking food and fashioning tools--they quickly came around. People have always feared the unknown. But if a tool proves sound and benefits individuals in some tangible way, they'll eagerly embrace it. One technology that people are currently on the fence about--particularly in the enterprise space--is conversational artificial intelligence (AI).

Key Points: – Access to appropriate domain data is the dominant factor in determining speech recognition performance. For this reason, Watson offers a cloud-based API with a general model with the option to customize. This allows the client to maintain control of their critical private and proprietary information. Automatic speech recognition, the ability to identify words and phrases in spoken language and converting them to text in real-time, provides nearly endless opportunities for the humans that use these AI systems, from improving customer satisfaction or enabling remote communication between doctors and patients to improving accessibility for the deaf or the blind. Platforms and applications built on automatic speech recognition are only as good as the system's understanding of language, and the way this understanding is measured. Achieving human parity, meaning an error rate on-par with that of a human listening to two people in conversation, has long remained a significant industry challenge – as has measuring it consistently.

Tesla is suing its former Autopilot director, claiming he took confidential, proprietary information about its self-driving technology and destroyed evidence to cover his tracks, according to a lawsuit filed in Santa Clara Superior Court. It alleges Sterling Anderson also attempted to recruit at least a dozen employees, in violation of his contract, all in an attempt to create a competing autonomous vehicle startup called "Aurora." Also named in the suit is Google's former self-driving director Chris Urmson, Anderson's partner in the venture. Tesla's Model S and Model X vehicles have an autonomous driving system that gathers data from a dozen ultrasonic sensors, a camera and radar, in conjunction with GPS data. The company just rolled out a new Autopilot update that gives the vehicles even more autonomous capability. Ex-Googler Urmson is reportedly an advocate of fully self-driving vehicles, having lobbied congress to allow cars on public roads without pedals or a steering wheel.