In the post-pandemic, post-Brexit world, businesses of all sorts face a range of new challenges – and many will be wondering if AI-based automation could help them win through. From adding more self-service capabilities for hotel guests through modernising e-commerce fulfilment to replacing missing workers in farming, the opportunities are many, but so are the pitfalls. Given all this, some research that we carried out last year on attitudes to AI – and in particular its subset, machine learning (ML) – is looking even more relevant now than it was then. It gives a picture not just of where AI could add value, but of key routes to get there and of hurdles that must be overcome along the way. As well as asking how our respondents perceived AI and ML, and hearing a lot of weariness with the noise and hype, we asked how well their organisations understood "the AI imperative".
Consumer privacy has made big headlines in the recent years with the Facebook Cambridge Analytica Scandal, Europe's GDPR and high-profile breaches by companies like Equifax. It's clear that the data of millions of consumers is at risk every day, and that companies that wish to handle their data must do so with the highest degree of protection around both security and privacy of that data, especially for companies that build and sell AI-enabled facial recognition solutions. As CEO of an AI-enabled software company specializing in facial recognition solutions, I've made data security and privacy among my top priorities. Our pro-privacy stance goes beyond mere privacy by design engineering methodology. We regularly provide our customers with education and best practices, and we have even reached out to US lawmakers, lobbying for sensible pro-privacy regulations governing the technology we sell.
One of NVIDIA's many different artificial intelligence projects (and by far the best one to date) lets you envision what your pet might look like it it were a meerkat. In case you didn't know, NVIDIA has its own research group dedicated solely to research into AI, and that includes developing new AI systems and agents which can do some pretty neat things. As the researchers say, although they take AI research very seriously, there's still no excuse not to have some fun with the products of their labors. It's the name given to an AI system they developed around a year ago which can generate a selection of images that are sorts of translations of your own pet's face into what said pet might look like if they were other types of animals. "With GANimal, you can bring your pet's alter ego to life by projecting their expression and pose onto other animals," explain the developers.
California is one of the hardest-hit states when it comes to coronavirus with more than 200,000 total cases. Data scientists seeking ways to help the state reopen the economy participated in a two-week 2020 COVID-19 Computational Challenge (CCC) in mid-June. The challenge was to provide guidance for risk mitigation for Los Angeles County. Additionally, the solution "must incorporate the ethical protection of individual data and respect data privacy norms." The winning teams revealed location-based COVID-19 exposure at different L.A. communities, developed apps for people to calculate their potential for infection, and delivered applicable data-driven recommendations along with L.A.'s reopening stages, officials said.
The ban comes after civil liberties groups highlighted what they described as faults in facial recognition algorithms after NIST found most facial recognition software was more likely to misidentify people of colour than white people. The Boston ban follows a ban imposed by San Francisco on the use of face recognition technology last year. The ban prevents any city employee using facial recognition or asking a third party to use the technology on its behalf. Boston's police department said it had not used the technology over what it called reliability fears, though it's clear the best systems are reasonably accurate in average working conditions. Critics also opposed the technology on the basis it might discourage citizens' rights to protest.
In 1963, Martin Luther King gave his "I have a dream" speech, words that reflected the thoughts and attitudes of civil rights activists at the time, and lit a torch that lives on in the hearts and minds of those who fight for civil liberties and equality in the western hemisphere. While the world has advanced since Dr. King ushered those words, it's hard to deny that discrimination still rears its ugly head in modern society. We know for a fact that racial discrimination in the workplace is illegal in most of America and Europe. And yet, just in the USA statistics show that things don't seem to have improved regarding hiring practices for black people and Hispanics in the last 25 years. In theory, AI-assisted hiring is built on an underlying model that makes unbiased decisions as long as the data itself isn't biased.
The federal government continues its halting effort to field an enterprise cloud strategy, with Lt. Gen. Jack Shanahan, who leads the Defense Department's Joint AI Center (JAIC), commenting recently that not having an enterprise cloud platform has made the government's efforts to pursue AI more challenging. "The lack of an enterprise solution has slowed us down," stated Shanahan during an AFCEA DC virtual event held on May 21, according to an account in FCW. However, "the gears are in motion" with the JAIC using an "alternate platform" for example to host a newer anti-COVID effort. This platform is called Project Salus, and is a data aggregation that is able to employ predictive modeling to help supply equipment needed by front-line workers. The Salus platform was used for the ill-fated Project Maven, a DOD effort that was to employ AI image recognition to improve drone strike accuracy.
Each Fourth of July for the past five years I've written about AI with the potential to positively impact democratic societies. I return to this question with the hope of shining a light on technology that can strengthen communities, protect privacy and freedoms, or otherwise support the public good. This series is grounded in the principle that artificial intelligence can is capable of not just value extraction, but individual and societal empowerment. While AI solutions often propagate bias, they can also be used to detect that bias. As Dr. Safiya Noble has pointed out, artificial intelligence is one of the critical human rights issues of our lifetimes.
Bottom Line: Barclays' and Kount's co-developed new product, Barclays Transact reflects the future of how companies will innovate together to apply AI-based fraud prevention to the many payment challenges merchants face today. Merchant payment providers have seen the severity, scope, and speed of fraud attacks increase exponentially this year. Account takeovers, card-not-present fraud, SMS spoofing, and phishing are just a few of the many techniques cybercriminals are using to defraud merchants out of millions of dollars. But it doesn't have to be a choice between security and a frictionless transaction. Frustrated by the limitations of existing fraud prevention systems, many payment providers are working as fast as they can to pilot AI- and machine-learning-based applications and platforms.
Fraym is using artificial intelligence and machine learning to help aid organizations in Africa and South Asia identify populations at risk due to Covid-19 using new geospatial visualizations. Fraym identifies high-risk populations and how to best communicate with them – making it an invaluable tool for more than 40 organizations and governments fighting the pandemic, including the Nigerian CDC, Kenyan presidential office, Zambian public health policymakers and aid organizations in Pakistan. Fraym has mapped communities based on concentrations of common transmission variables and then combined this with data from household surveys and remote sensing data, to then understand how these individuals consume news at a hyper-local level. The company is providing this information, which is at a 1-square kilometer level, for free to help fight the spread of Covid19. Since March 2020, Fraym has produced more than 300 COVID-19 related data layers in nearly 20 different countries.