Written by Chris Anley, Chief Scientist, NCC Group This paper collects a set of notes and research projects conducted by NCC Group on the topic of the security of Machine Learning (ML) systems. The objective is to provide some industry perspective to the academic community, while collating helpful references for security practitioners, to enable more effective security auditing and security-focused code review of ML systems. Details of specific practical attacks and common security problems are described. Some general background information on the broader subject of ML is also included, mostly for context, to ensure that explanations of attack scenarios are clear, and some notes on frameworks and development processes are provided. This paper collects a set of notes and research projects conducted by NCC Group on the topic of the security of Machine Learning (ML) systems.

I have long been intrigued by archaeogaming--an academic discipline that explores the fusion of archaeological objects, methods, and characters into video games. So I was thrilled when the video game company Ubisoft released Assassin's Creed: Origins, set in Egypt during Cleopatra's reign. The designers collaborated with Egyptologists to ensure everything from the architecture to the hieroglyphics created an accurate, immersive world. Unexpectedly, this partnership inspired a machine-learning spinoff that changed the course of my early career. While working with Egyptologists, the game developers learned that translating and interpreting ancient hieroglyphic texts is time-consuming, and the process has changed little in the last century.

Six months after star AI ethics researcher Timnit Gebru said Google fired her over an academic paper scrutinizing a technology that powers some of the company's key products, the company says it's still deeply committed to ethical AI research. It promised to double its research staff studying responsible AI to 200 people, and CEO Sundar Pichai has pledged his support to fund more ethical AI projects. Jeff Dean, the company's head of AI, said in May that while the controversy surrounding Gebru's departure was a "reputational hit," it's time to move on. But some current members of Google's tightly knit ethical AI group told Recode the reality is different from the one Google executives are publicly presenting. The 10-person group, which studies how artificial intelligence impacts society, is a subdivision of Google's broader new responsible AI organization.

Elon Musk's Neuralink has been making waves on the technology side of neural implants, but it hasn't yet shown how we might actually use implants. For now, demonstrating the promise of implants remains in the hands of the academic community. This week, the academic community provided a rather impressive example of the promise of neural implants. Using an implant, a paralyzed individual managed to type out roughly 90 characters per minute simply by imagining that he was writing those characters out by hand. Previous attempts at providing typing capabilities to paralyzed people via implants have involved giving subjects a virtual keyboard and letting them maneuver a cursor with their mind.

After decades of debate on the feasibility of open access (OA) to scientific publications, we may be nearing a tipping point. A number of recent developments, such as Plan S, suggest that OA upon publication could become the default in the sciences within the next several years. Despite uncertainty about the long-term sustainability of OA models, many publishers who had been reluctant to abandon the subscription business model are showing openness to OA (1). Although more OA can mean more immediate, global access to scholarship, there remains a need for practical, sustainable models, for careful analysis of the consequences of business model choices, and for "caution in responding to passionate calls for a'default to open'" (2). Of particular concern for the academic community, as subscription revenues decline in the transition to OA and some publishers prioritize other sources of revenue, is the growing ownership of data analytics, hosting, and portal services by large scholarly publishers.

We are living through a new industrial revolution in which artificial intelligence (AI) and machine learning (ML) permeate all industries and sectors of our economy, enhancing the impact and value of businesses worldwide. The UK has acknowledged this, and consequently is heavily investing in these technologies. But despite numerous successes, there have also been many failed AI projects that simply did not provide the expected return on investment. In many cases, the reasons for these failures are mismatched expectations and the overselling of AI's capabilities. Businesses must be better informed and trained to understand the limitations and expectations of what can be achieved when harnessing AI to solve their problems.

In 2015, Uber opened a research facility around the corner from Carnegie Mellon University's National Robotics Engineering Center in a move positioned as a partnership between the two organizations. Within months, dozens of faculty members had left their positions for full-time roles at Uber, draining the center of much of its talent. Other major tech companies have followed a similar path – in 2018, Facebook launched AI labs in Seattle and Pittsburgh headed by former professors. These stories provide a window into a tug-of-war that's been playing out between the tech industry and academia. Keen to build products and services that use AI and machine learning, tech firms and other businesses have been hiring away researchers and professors from universities, creating a shortage of academics who can teach the next generation of data scientists. The proportion of computer science PhDs who stay in academia has reached a "historic low," the Computing Research Association has said.

Google CEO Sundar Pichai answered a lot of questions about anti-conservative bias. Google CEO Sundar Pichai answered a lot of questions about anti-conservative bias. Google CEO Sundar Pichai answered a lot of questions about anti-conservative bias. Google CEO Sundar Pichai answered a lot of questions about anti-conservative bias. Google CEO Sundar Pichai, head of one of the world's leading artificial intelligence companies, said in an interview this week that concerns about harmful applications of the technology are "very legitimate" - but the tech industry should be trusted to responsibly regulate its use.

Google CEO Sundar Pichai, head of one of the world's leading artificial intelligence companies, said in an interview this week that concerns about harmful applications of the technology are "very legitimate" - but the tech industry should be trusted to responsibly regulate its use. Speaking with The Washington Post on Tuesday afternoon, Pichai said that new AI tools - the backbone of innovations such as driverless cars and disease-detecting algorithms - require companies to set ethical guardrails and think through how the technology can be abused. "I think tech has to realise it just can't build it, and then fix it," Pichai said. "I think that doesn't work." Tech giants have to ensure that artificial intelligence with "agency of its own" doesn't harm humankind, Pichai said.

Never before have the fundamental assumptions about the U.S. job market looked so precarious. Automation, artificial intelligence, and robotics, among other technologies, are changing the skills and the skill level required of employees in many industries, including retail, transportation, and manufacturing. The accounting profession is experiencing similar changes, and the pace and pressure of that change is exploding into a major disruption. Robotics is expected to eliminate 40 percent of basic accounting work by 2020. We're in the early stages of the big data and artificial intelligence revolution in accounting, which already is being wholeheartedly embraced at the larger firms.