AI to Profile Gang Members on Twitter
November 16, 2016
Researchers from Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis) are claiming that an algorithm developed by them is capable of identifying gang members on Twitter.
Vice.com recently published an article titled Researchers Claim AI Can Identify Gang Members on Twitter, which claims that:
A deep learning AI algorithm that can identify street gang members based solely on their Twitter posts, and with 77 percent accuracy.
The article then points out the shortcomings of the algorithm or AI by saying this:
According to one expert contacted by Motherboard, this technology has serious shortcomings that might end up doing more harm than good, especially if a computer pegs someone as a gang member just because they use certain words, enjoy rap, or frequently use certain emojis—all criteria employed by this experimental AI.
The shortcomings do not end here. The data on Twitter is being analyzed in a silo. For example, let us assume that few gang members are identified using the algorithm (remember, no location information is taken into consideration by the AI), what next?
Is it not necessary then to also identify other social media profiles of the supposed gang members, look at Big Data generated by them, analyze their communication patterns and then form some conclusion? Unfortunately, none of this is done by the AI. It, in fact, would be a mammoth task to extrapolate data from multiple sources just to identify people with certain traits.
And most importantly, what if the AI is put in place, and someone just for the sake of fun projects an innocent person as a gang member? As rightly pointed out in the article – machines trained on prejudiced data tend to reproduce those same, very human, prejudices.
Vishal Ingole, November 16, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Lawyers Might Be Automated Too
November 14, 2016
The worry with artificial intelligence is that it will automate jobs and leave people without a way to earn income. The general belief is that AI will automate manufacturing, retail, food service, and other industries, but what about law? One would think that lawyers would never lose their jobs, because a human is required to navigate litigation and represent a person in court, right? According to The Inquirer article, “UCL Creates AI ‘Lawbot’ That Rules on Cases With Surprising Accuracy” lawyers might be automated too.
On a level akin to Watson, researchers at University College London, led by Dr. Nikoalos Aletras, created an algorithm that peruses case information and can predict accurate verdicts. The UCL team fed the algorithm litigation information from cases about torture, degrading treatment, privacy, and fair trials. They hope the algorithm will be used to identify patterns in human rights abuses.
Dr. Aletras does not think AI will replace judges and lawyers, but it could be used as a tool to identify patterns in cases with specific outcomes. The algorithm has a 79% accuracy rate, which is not bad considering the amount of documentation involved. Also the downside is:
At a wider level, although 79 percent is a bit more ED-209 than we’d like for now, it does suggest that we’re a long way towards being able to install an ethical and moral code that would allow AI to … you know, not kill us and that. With so many doomsayers warning us that the closer that we get to the so-called ‘singularity’ between humans and machines, the more likely we are to be toast as a race, it’s something of a good news story to see what’s being done to ensure AI stays on the straight and narrow.
Automation in the legal arena is a strong possibility for when “…implementation and interpretation of the law that is required, less so than the fact themselves.” The human element is still needed to decide cases, but perhaps it would cut down on the amount of light verdicts for pedophiles, sex traffickers, rapists, and other bad guys. It does make one wonder what alternative fields lawyers would consider?
Whitney Grace, November 14, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Partnership Aims to Establish AI Conventions
October 24, 2016
Artificial intelligence research has been booming, and it is easy to see why— recent advances in the field have opened some exciting possibilities, both for business and society as a whole. Still, it is important to proceed carefully, given the potential dangers of relying too much on the judgement of algorithms. The Philadelphia Inquirer reports on a joint effort to develop some AI principles and best practices in its article, “Why This AI Partnership Could Bring Profits to These Tech Titans.” Writer Chiradeep BasuMallick explains:
Given this backdrop, the grandly named Partnership on AI to Benefit People and Society is a bold move by Alphabet, Facebook, IBM and Microsoft. These globally revered companies are literally creating a technology Justice League on a quest to shape public/government opinion on AI and to push for friendly policies regarding its application and general audience acceptability. And it should reward investors along the way.
The job at hand is very simple: Create a wave of goodwill for AI, talk about the best practices and then indirectly push for change. Remember, global laws are still obscure when it comes to AI and its impact.
Curiously enough, this elite team is missing two major heavyweights. Apple and Tesla Motors are notably absent. Apple Chief Executive Tim Cook, always secretive about AI work, though we know about the estimated $200 million Turi project, is probably waiting for a more opportune moment. And Elon Musk, co-founder, chief executive and product architect of Tesla Motors, has his own platform to promote technology, called OpenAI.
Along with representatives of each participating company, the partnership also includes some independent experts in the AI field. To say that technology is advancing faster than the law can keep up with is a vast understatement. This ongoing imbalance underscores the urgency of this group’s mission to develop best practices for companies and recommendations for legislators. Their work could do a lot to shape the future of AI and, by extension, society itself. Stay tuned.
Cynthia Murrell, October 24, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Pattern of Life Analysis to Help Decrypt Dark Web Actors
October 18, 2016
Google funded Recorded Future plans to use technologies like natural language processing, social network analysis and temporal pattern analysis to track Dark Web actors. This, in turn, will help security professionals to detect patterns and thwart security breaches well in advance.
An article Decrypting The Dark Web: Patterns Inside Hacker Forum Activity that appeared on DarkReading points out:
Most companies conducting threat intelligence employ experts who navigate the Dark Web and untangle threats. However, it’s possible to perform data analysis without requiring workers to analyze individual messages and posts.
Recorded Future which deploys around 500-700 servers across the globe monitors Dark Web forums to identify and categorize participants based on their language and geography. Using advanced algorithms, it then identifies individuals and their aliases who are involved in various fraudulent activities online. This is a type of automation where AI is deployed rather than relying on human intelligence.
The major flaw in this method is that bad actors do not necessarily use same or even similar aliases or handles across different Dark Web forums. Christopher Ahlberg, CEO of Recorded Future who is leading the project says:
A process called mathematical clustering can address this issue. By observing handle activity over time, researchers can determine if two handles belong to the same person without running into many complications.
Again, researchers and not AI or intelligent algorithms will have to play a crucial role in identifying the bad actors. What’s interesting is to note that Google, which pretty much dominates the information on Open Web is trying to make inroads into Dark Web through many of its fronts. The question is – will it succeed?
Vishal Ingole, October 18, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Artificial Intelligence Is Only a Download Away
October 17, 2016
Artificial intelligence still remains a thing of imagination in most people’s minds, because we do not understand how much it actually impacts our daily lives. If you use a smartphone of any kind, it is programmed with software, apps, and a digital assistant teeming with artificial intelligence. We are just so used to thinking that AI is the product of robots that we are unaware our phones, tablets, and other mobiles devices are little robots of their own.
Artificial intelligence programming and development is also on the daily task list on many software technicians. If you happen to have any technical background, you might be interested to know that there are many open source options to begin experimenting with artificial intelligence. Datamation rounded up the “15 Top Open Source Artificial Intelligence Tools” and these might be the next tool you use to complete your machine learning project. The article shares that:
Artificial Intelligence (AI) is one of the hottest areas of technology research. Companies like IBM, Google, Microsoft, Facebook and Amazon are investing heavily in their own R&D, as well as buying up startups that have made progress in areas like machine learning, neural networks, natural language and image processing. Given the level of interest, it should come as no surprise that a recent artificial intelligence report from experts at Stanford University concluded that ‘increasingly useful applications of AI, with potentially profound positive impacts on our society and economy are likely to emerge between now and 2030.
The statement reiterates what I already wrote. The list runs down open source tools, including PredictionIO, Oryx 2, OpenNN, MLib, Mahout, H20, Distributed Machine Learning Toolkit, Deeplearning4j, CNTK, Caffe, SystemML, TensorFlow, and Torch. The use of each tool is described and most of them rely on some sort of Apache software. Perhaps your own artificial intelligence project can contribute to further development of these open source tools.
Whitney Grace, October 17, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
A Literary Magazine by a Machine?
October 14, 2016
Literary magazines are a great way to read short stories, the latest poetry, and other compelling pieces by a variety of authors. What if those authors are machines? CuratedAI is the first literary magazine written by machines for human readers. Computers are presented as sterile, uncreative items, but technology programmed with machine learning and content curation can actually write some decent pieces.
Here is the magazine’s mission statement:
“CuratedAI is a literary magazine with a twist– all stories and poems are generated by machines using the tricks of the Artificial Intelligence trade. Editing, for now, is still the domain of us humans, but we aim to keep our touch as light as possible.”
Poetry is a subjective literary form and perhaps the most expressive. It allows writers to turn words into art and stray away from standard language rules. In other words, it is the perfect form for computers. They insert adjectives wherever the algorithm states and the sentences do not always make sense.
Prose, on the other mouse, is not its best form. The stories read like a bad Internet translation from Japanese to English. It will be some time before computers are writing comprehensible novels, at least for some of them. Machine learning was used in Japan for a novel writing contest and the machine that wrote the book, actually won a prize. So machine cans write prize-winning literature.
However, no one can program imagination…not yet anyway.
Whitney Grace, October 14, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Microsoft Considers next Generation Artificial Intelligence
August 24, 2016
While science fiction portrays artificial intelligence in novel and far-reaching ways, certain products utilizing artificial intelligence are already in existence. WinBeta released a story, Microsoft exec at London conference: AI will “change everything”, which reminds us of this. Digital assistants like Cortana and Siri are one example of how mundane AI can appear. However, during a recent AI conference, Microsoft UK’s chief envisioning officer Dave Choplin projected much more impactful applications. This article summarizes the landscape of concerns,
Of course, many also are suspect about the promise of artificial intelligence and worry about its impact on everyday life or even its misuse by malevolent actors. Stephen Hawking has worried AI could be an existential threat and Tesla CEO Elon Musk has gone on to create an open source AI after worrying about its misuse. In his statements, Choplin also stressed that as more and more companies try to create AI, ‘We’ve got to start to make some decisions about whether the right people are making these algorithms.
There is much to consider in regards to artificial intelligence. However, such a statement about “the right people” cannot stop there. Choplin goes on to refer to the biases of people creating algorithms and the companies they work for. Because organizational structures must also be considered, so too must their motivator: the economy. Perhaps machine learning to understand the best way to approach AI would be a good first application.
Megan Feil, August 24, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
The Less Scary Applications of Artificial Intelligence: Computer Vision
August 3, 2016
The article on The Christian Science Monitor titled Shutterstock’s Reverse Image Search Promises a Gentler Side of AI provides a glimpse into computer vision, or the way a computer assesses and categorizes any image into its parts. Shutterstock finds that using machine learning to find other images similar to the first is a vast improvement, because rather than analyzing keywords, AI analyzes the image directly based on exact colors and shapes. The article states,
“That keyword data, while useful for indexing images into categories on our site, wasn’t nearly as effective for surfacing the best and most relevant content,” says Kevin Lester, vice president of engineering at the company, in a blog post. “So our computer vision team worked to apply machine learning techniques to reimagine and rebuild that process.”
The neural network has now examined 70 million images and 4 million video clips in its collection.”
In addition, the company plans to expand the search feature to videos as well as images. Jon Oringer, CEO and founder of Shutterstock, has a vision of endless possibilities for this technology. The article points out that this is one of the clearly positive effects of AI, which gets a bad rap, perhaps not unfairly, given the potential for autonomous weapons and commercial abuse. So by all means, let’s use AI to recognize a cat, like Google, or to analyze images.
Chelsea Kerwin, August 3, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Google DeepMind AI Project Makes Progress
July 25, 2016
For anyone following the development of artificial intelligence, I recommend checking out the article, “How Google Plans to Solve Artificial Intelligence” at MIT Technology Review. The article delves into Google’s DeepMind project, an object of renewed curiosity after its AlphaGo software bested the human world champion of the ancient game Go in March.
This Go victory is significant, because it marks progress beyond the strategy of calculating different moves’ possible outcomes; the game is too complex for that established approach (though such calculations did allow IBM’s DeepBlue to triumph over the world chess champion in 1997). The ability to master Go has some speaking of “intuition” over calculation. Just how do you give software an approximation of human intuition? Writer Tom Simonite tells us:
“Hassabis believes the reinforcement learning approach is the key to getting machine-learning software to do much more complex things than the tricks it performs for us today, such as transcribing our words, or understanding the content of photos. ‘We don’t think just observing is enough for intelligence, you also have to act,’ he says. ‘Ultimately that’s the only way you can really understand the world.’”
“DeepMind’s 3-D environment Labyrinth, built on an open-source clone of the first-person-shooter Quake, is designed to provide the next steps in proving that idea. The company has already used it to challenge agents with a game in which they must explore randomly generated mazes for 60 seconds, winning points for collecting apples or finding an exit…. Future challenges might require more complex planning—for example, learning that keys can be used to open doors. The company will also test software in other ways, and is considering taking on the video game Starcraft and even poker. But posing harder and harder challenges inside Labyrinth will be a major thread of research for some time, says Hassabis. “It should be good for the next couple of years,” he says.”
The article has a video of DeepMind’s virtual labyrinth you can check out, if you’re curious. (It looks very much like an old Windows screen saver some readers may recall.) Simonite tells us that AI firms across the industry are watching this project carefully. He also points to some ways DeepMind is already helping with real-world problems, like developing training software with the U.K.’s National Health Service to help medical personnel recognize commonly missed signs of kidney problems.
See the article for much more about Google’s hopes and plans for DeepMind. Simonite concludes by acknowledging the larger philosophical and ethical concerns around artificial intelligence. We’re told DeepMind has its own “internal ethics board of philosophers, lawyers, and businesspeople.” I think it is no exaggeration to say these folks, whom Google indicates it will name someday soon, could have great influence over the nature of our future technology. Let us hope Google chooses wisely.
Cynthia Murrell, July 25, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
There is a Louisville, Kentucky Hidden Web/Dark Web meet up on July 26, 2016. Information is at this link: http://bit.ly/29tVKpx.
The Machine Learning Textbook
July 19, 2016
Deep learning is another bit of technical jargon floating around and it is tied to artificial intelligence. We know that artificial intelligence is the process of replicating human thought patterns and actions through computer software. Deep learning is…well, what specifically? To get a primer on what deep learning is as well as it’s many applications check out “Deep Learning: An MIT Press Book” by Ian Goodfellow, Yoshua Bengio, and Aaron Courville.
Here is how the Deeping Learning book is described:
“The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free. The print version will be available for sale soon.”
This is a fantastic resource to take advantage of. MIT is one of the leading technical schools in the nation, if not the world, and the information that is sponsored by them is more than guaranteed to round out your deep learning foundation. Also it is free, which cannot be beaten. Here is how the book explains the goal of machine learning:
“This book is about a solution to these more intuitive problems. This solution is to allow computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept de?ned in terms of its relation to simpler concepts. By gathering knowledge from experience, this approach avoids the need for human operators to formally specify all of the knowledge that the computer needs.”
If you have time take a detour and read the book, or if you want to save time there is always Wikipedia.
Whitney Grace, July 19, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
There is a Louisville, Kentucky Hidden Web/Dark
Web meet up on July 26, 2016.
Information is at this link: http://bit.ly/29tVKpx.
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