Welcome back to another glorious episode of CTRL T. This week, Henry Pickavet and I explore Amazon's new cashier-less stores that promise no waiting in line -- except to get in -- and Uber's newest C-level executive hire. Full disclosure, I went to USC but Noble was not a professor there at the time. Additional disclosure, I wish I could have had her as a teacher because she's smart as hell. Final disclosure, Henry applied to USC but was rejected. In her book, Noble discusses the ways in which algorithms are biased and perpetuate racism.

As a teenager in Nigeria, I tried to build an artificial intelligence system. I was inspired by the same dream that motivated the pioneers in the field: That we could create an intelligence of pure logic and objectivity that would free humanity from human error and human foibles. I was working with weak computer systems and intermittent electricity, and needless to say my AI project failed. Eighteen years later -- as an engineer researching artificial intelligence, privacy and machine-learning algorithms -- I'm seeing that so far, the premise that AI can free us from subjectivity or bias is also disappointing. We are creating intelligence in our own image.

Check out the full schedule at the Strata Data Conference in New York, September 11-13, 2018. Interest in machine learning (ML) has been growing steadily, and many companies and organizations are aware of the potential impact these tools and technologies can have on their underlying operations and processes. The reality is that we are still in the early phases of adoption, and a majority of companies have yet to deploy ML across their operations. In this post, I'll describe how one can go from "exploration and evaluation" to actual "implementation" of ML technologies. Along the way, I'll highlight key sections of the upcoming Strata Data conference in New York this September.

Artificial intelligence will change the world. Because so many people and companies believe this, AI and the entire technological ecosystem in which it functions are highly valuable to private-sector organizations and nation-states. That means that nations will try to identify, steal, and corrupt or otherwise counteract the AI and related assets of others, and will use AI against each other in pursuit of their own national interests. And that presents the United States and its allies with a classic counterintelligence problem in a novel and high-stakes context: How do we protect a valuable national asset against a range of threats from hostile foreign actors, and how do we protect ourselves against the threat from AI in the hands of adversaries? In the broad and diverse discussion of artificial intelligence in the global technological and economic infrastructure of the future, this question has received remarkably little attention. In this post and others to follow, I will endeavor to explore some of the counterintelligence risks and problems presented by AI and the AI ecosystem. I'll first talk about the general problem of AI and counterintelligence and then, in later posts, dive into some of the specific areas that cause me the greatest concern in this sphere. Technological advancements often change society.

BOGOTÁ, Colombia--With drug crops booming, Colombia's police are busily testing whether drones carrying defoliants can efficiently kill the leaf used to make cocaine and win the support of Trump administration officials concerned about this country's growing capacity to supply drugs to American consumers. Antidrug officials here say that in recent weeks they have deployed 10 drones, each weighing 50 pounds when loaded with herbicide, in southwest Nariño province. The small, remotely guided aircraft destroyed hundreds of acres of coca in a first round of tests, said police and the company contracted by the government to supply the drones. Colombia's new president, Iván Duque, said that he wants some kind of aerial fumigation of coca fields, which expanded 160% to 516,000 acres from 2012 to 2017, the White House reported in June. But he prefers drones over planes to drop the herbicide, which would mitigate damage to legal crops growing adjacent to coca fields.

There has been a huge resurgence of interest in Artificial Intelligence – but what does this mean for the law?

In 1955, science fiction writer Isaac Asimov published a short story about an experiment in "electronic democracy," in which a single citizen, selected to represent an entire population, responded to questions generated by a computer named Multivac. The machine took this data and calculated the results of an election that therefore never needed to happen. Asimov's story was set in Bloomington, Indiana, but today an approximation of Multivac is being built in China. For any authoritarian regime, "there is a basic problem for the center of figuring out what's going on at lower levels and across society," says Deborah Seligsohn, a political scientist and China expert at Villanova University in Philadelphia. How do you effectively govern a country that's home to one in five people on the planet, with an increasingly complex economy and society, if you don't allow public debate, civil activism, and electoral feedback?

The test, which was conducted by ACLU of Northern California to check its efficiency in facial recognition, included a wide range of datasets -- of men, women, legislators, Republicans, Democrats of all ages from across the country. The ACLU in a statement had said that it had used exact same facial recognition system that Amazon offers to the public, which anyone could use to scan for matched between images of faces. The running of entire test had cost them a meager $12.33.

In the final article of Information Age's three part series on artificial intelligence in the legal industry, we look at how law firms can adopt AI and if AI represents the future of law. This series has been taken an extensive look – with the help of Geoffrey Vance, the chair of Perkins Coie's E-Discovery Services and Strategy Practice, and Alvin Lindsay, partner at Hogan Lovells – at how technology can disrupt a traditional industry, and emphasised the point that'every company is a technology company'. In the first of this three part series on AI in legal industry, we looked at what the stage of AI adoption in law, and how it is – if at all – creating a more strategic role for associates in law firms. The article established that AI adoption was at a fairly early stage, although its use is not a new phenomenon. It also became clear that, as suggested by a report from ALM Intelligence, AI will be crucial in helping law firms overcome challenges and survive moving forward.

Drones aren't just cracking down on land-based poaching in Africa -- ATLAN Space is launching a pilot that will use autonomous drones to report illegal fishing in the Seychelles islands. The fliers will use computer vision to identify both the nature of boats in protected waters as well as their authorization. If they detect illegal fishing boats, the drones will note vessel locations, numbering and visible crews, passing the information along to officials. The pilot starts in October. The technology won't be limited to any specific drone system, ATLAN Space added, and that's important for the fishing industry.