The recent data breach of India-based technology services provider Wipro serves as yet another reminder that technology or outsourcing service providers are high-priority targets for cyberattacks. In “Managing Risk in Light of the Wipro Data Breach,” colleagues Meighan E. O’Reardon, Andrew Caplan, Mia Rendar and
In what is a challenging sector—especially following recent revelations over “secretive” government-awarded post-Brexit contracts—the UK Government recently issued new guidance on outsourcing aimed at improving government procurement and delivering better public service. Released on February 20, 2019, the “Outsourcing Playbook” targets improvements in how government works with industry and delivers better public services, but there are lessons to be learned for the private sector, as well.
Financial institutions regulated by the New York Department of Financial Services (DFS)—referred to in this post as “Covered Entities”—should by now be well familiar with the department’s sweeping cybersecurity regulation, 23 NYCRR 500, that became effective on March 1, 2017. The regulation delves into a level of detail (e.g., multi-factor authentication and encryption requirements) and requires a level of senior level attention (e.g., annual attestation of compliance, signed by the Board of Directors or a Senior Officer) heretofore unseen in U.S. federal or state regulations.
When it comes to artificial intelligence, a lack of transparency in process and bad data to begin with are two of the issues most hampering the embrace by the boardroom. In AI: Black boxes and the boardroom, colleagues Tim Wright and Antony Bott examine how the resulting lack of trust can make companies wary of the AI technology despite its many potential benefits, and some basic steps one can take to alleviate those concerns.
According to research conducted by the International Labour Organisation, more than 40 million people worldwide were victims of modern slavery in 2016, and about 152 million children, aged between five and 17, were subject to child labour.
Agile is emerging as the prevailing methodology for software development. According to the 12th Annual State of Agile Report, a survey conducted by VersionOne and published earlier this year, 97% of respondent organizations practice Agile development methods, while 52% reported that more than half of the development teams in their organizations are following Agile practices.
Digital advertising is exploding. In just the first six months of 2017 alone, internet advertising revenues exceeded $40 billion. Promoted ads are dominating social media platforms like Facebook and Twitter, and it is impossible to surf the internet or use mobile apps without having to watch or click through a myriad of dynamic ads to get to the underlying content. Why is this? Because digital advertising works.
Outsourcing service providers have long been in the practice of bringing highly skilled employees from India and other locations to work with local businesses within the United States. Outsourcers such as Wipro, TCS and Infosys are some the largest petitioners of H-1B visas, the high-skilled work visa favored by the tech industry. In order to bring the most value to customers, service providers largely rely on getting work visas for Indian tech workers so they can consult with U.S. businesses.
At a recent seminar discussion on smart buildings, I was reminded of the Mr. Robot episode where the general counsel of a multinational corporation, which is being targeted by a hacker group, has her futuristic apartment hacked. In case you haven’t been watching, Mr. Robot is USA Network’s psychological thriller about a young programmer who works as a cybersecurity engineer by day but by night is a vigilante hacker.
Famously dramatized by the disembodied voice of HAL in Stanley Kubrick’s 1968 film 2001: A Space Odyssey, artificial intelligence has been the subject of humanity’s existential angst for decades. Although Elon Musk warns that those fears may be justified, one of the biggest pushes for advancing artificial intelligence to-date has been to market it for purposes of day-to-day corporate efficiency. Nearly every IT vendor is seeking to make a name for their proprietary AI tool by offering AI as a Service to the majority of businesses who are not developing AI in-house, but who want to leverage the benefits of AI’s automated decision-making, data analytics and cost-savings. In the business context, AI has yet to pose the threat of refusing to “open the pod bay doors,” but customers are faced with the challenge of exposing the vendor’s AI to data amassed by their entire enterprise, thereby allowing the algorithms to learn from and evolve based on information that may be private, proprietary and heavily regulated. The most common solution to this conundrum is for customers to contract for ownership of all machine learning models, bots and other outputs that result from the AI’s presence in the customer’s environment and processing of customer data. But what are the implications of this “all for one” approach to ownership of the fruits of machine learning? What, if any, innovations in AI are lost when lessons learned are retained by a single entity?
