Sunday, January 19, 2020


Your security has already been breached. Maybe.
Hacker leaks passwords for more than 500,000 servers, routers, and IoT devices
A hacker has published this week a massive list of Telnet credentials for more than 515,000 servers, home routers, and IoT (Internet of Things) "smart" devices.
The list, which was published on a popular hacking forum, includes each device's IP address, along with a username and password for the Telnet service, a remote access protocol that can be used to control devices over the internet.




Doom and gloom from Brookings? “It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of Light, it was the season of Darkness, it was the spring of hope, it was the winter of despair, we had everything before us, we had nothing before us...”
Whoever leads in artificial intelligence in 2030 will rule the world until 2100
We are on the cusp of colossal changes. But you don’t have to take Mr. Putin’s word for it, nor mine. This is what Erik Brynjolfsson, director of the MIT Initiative on the Digital Economy and a serious student of the effects of digital technologies, says:
“This is a moment of choice and opportunity. It could be the best 10 years ahead of us that we have ever had in human history or one of the worst, because we have more power than we have ever had before.”




Smile!
The Secretive Company That Might End Privacy as We Know It
Until recently, Hoan Ton-That’s greatest hits included an obscure iPhone game and an app that let people put Donald Trump’s distinctive yellow hair on their own photos.
Then Mr. Ton-That — an Australian techie and onetime model — did something momentous: He invented a tool that could end your ability to walk down the street anonymously, and provided it to hundreds of law enforcement agencies, ranging from local cops in Florida to the F.B.I. and the Department of Homeland Security.
His tiny company, Clearview AI, devised a groundbreaking facial recognition app. You take a picture of a person, upload it and get to see public photos of that person, along with links to where those photos appeared. The system — whose backbone is a database of more than three billion images that Clearview claims to have scraped from Facebook, YouTube, Venmo and millions of other websites — goes far beyond anything ever constructed by the United States government or Silicon Valley giants.
Federal and state law enforcement officers said that while they had only limited knowledge of how Clearview works and who is behind it, they had used its app to help solve shoplifting, identity theft, credit card fraud, murder and child sexual exploitation cases.




Before you architect…
Beyond the AI Hype: Four Factors Businesses Should Consider Before Investing in AI
The report, “Artificial Intelligence: A Framework to Identify Challenges and Guide Successful Outcomes,” analyzes in-depth the current state of artificial intelligence and provides companies with an outcome-focused framework that they can apply to make more successful investment decisions and better manage their AI projects.
Lux sees four major factors in making the right AI investments and decisions:
  1. Clearly understanding the outcomes implementing AI will provide for their business;
  2. Focusing on an AI product’s capabilities instead of flashy marketing;
  3. Knowing when the technology is mature enough to mitigate risk;
  4. Identifying practical challenges to both implementation and maintenance of the technology once it is in place.


(Related) Sometimes plodding is better. (Just to keep my students confused.)
Why Agile Methodologies Miss The Mark For AI & ML Projects
Agile methodologies are extremely popular for a wide range of application development purposes, and for good reason. Prior to the widespread adoption of Agile, many organizations found themselves bogged down by traditional “waterfall” methodologies that borrowed too much from assembly line methods of production. Rather than wait months or years for a software project to wind its way through design, development, testing, and deployment, the Agile approach focused on tight, short iterations with a goal of rapidly producing a deliverable to meet immediate needs of the business owner, and then continuously iterating as requirements and needs become more refined. To this end, the Agile Manifesto emphasizes focusing on individuals and interactions over strict processes and tools, delivery of working products over a focus on planning and documentation, continuous customer collaboration versus a drawn out contract negotiation process, and a focus on responding to change rather than strict adherence to a plan.
However, even Agile methodologies are challenged by the requirements of AI systems. For one, what exactly is being “delivered” in an AI project? You can say that the machine learning model is a deliverable, but it’s actually just an enabler of a deliverable, not providing any functionality in and of itself. In addition, if you dig deeper into machine learning models, what exactly is in the model? The model consists of algorithmic code plus training model data (if supervised), parameter settings, hyperparameter configuration data, and additional support logic and code that together comprises the model. Indeed, you can have the same algorithm with different training data and that would generate a different model, and you can have a different algorithm with the same training data and that would also generate a different model. So is the deliverable the algorithm, the training data, the model that aggregates them, the code that uses the model for a particular application, all of the above, none of the above? The answer is yes.




Ethical for humans, but not ethical for machines?
Human Ethics in the age of Robots and Artificial Intelligence
The granting of citizenship to a Robot, Sophia last year by Saudi Arabia and the development of robot babies are just a few instances of the rapid explosion of Robots and Artificial Intelligence across the world. As futurists believe, there would more integration of robots in our daily lives, possibly having robot physician, robot care giver, robot driver and even robots as partners. These leads to new ethical questions considered unimaginable before. This chapter through analysis of writings of different scholars in the field tries to look at a framework of ethics which would govern relationship between robots and humans in not so distant future.




Leave it to the AI lawyers?
Whether causing flash crashes in financial markets, purchasing illegal drugs, or running over pedestrians, AI is increasingly engaging in activity that would be criminal for a natural person, or even an artificial person like a corporation. We argue that criminal law falls short in cases where an AI causes certain types of harm and there are no practically or legally identifiable upstream criminal actors. This Article explores potential solutions to this problem, focusing on holding AI directly criminally liable where it is acting autonomously and irreducibly. Conventional wisdom holds that punishing AI is incongruous with basic criminal law principles such as the capacity for culpability and the requirement of a guilty mind. Drawing on analogies to corporate and strict criminal liability, as well as familiar imputation principles, we show how a coherent theoretical case can be constructed for AI punishment. AI punishment could result in general deterrence and expressive benefits, and it need not run afoul of negative limitations such as punishing in excess of culpability. Ultimately, however, punishing AI is not justified, because it might entail significant costs and it would certainly require radical legal changes. Modest changes to existing criminal laws that target persons, together with potentially expanded civil liability, are a better solution to AI crime.




Interesting perspective.
The Artificial Intelligence of European Union Law
In this Article, I take my chance to briefly introduce the key ideas of two German philosophers whose work is highly relevant for the rule of law in the age of machine intelligence. The current predominance of Anglo-American moral and legal philosophy, with its emphasis on either utilitarian or a specific type of neo-Kantian moral philosophy calls for some countervailing thinking, and the German Law Journal seems the right place to dare such a thing. The recent launch of an English translation of biologist and philosopher Helmuth Plessner’s seminal Levels of Organic Life and the Human (1928)1 invites a fundamental reflection on the difference between human and machine intelligence, including a penetrating criticism of the kind of behaviorism that underpins personalized micro targeting.2 The core findings of Plessner, based on what he calls the ex-centric positionality of human beings, connect well with key insights of lawyer and legal philosopher Gustav Radbruch, taken from his Legal Philosophy (1932),3 notably the idea that law is defined by antinomian goals.
AI usually stands for artificial intelligence, referring to a rather vague notion upon which no agreement exists, neither amongst experts nor amongst those affected by its supposedly disruptive character. Therefore, AI is better understood as referring to automated inferences and is better described as machine intelligence. Based on Plessner, I will argue that current machine intelligence is radically different from human intelligence. My point will be that it is precisely human intelligence that is deeply artificial, whereas machine intelligence is merely automated. This relates to the importance of recognizing, appreciating, and protecting the artificial nature of law and the specific intelligence it affords human society. Finally, I will argue that a proper understanding of the “mode of existence” of machinic agency will be one of the major challenges for the EU in the 2020s. If we get it right, we should be able to avoid the quest for certainty4 that informs both informational capitalism5 and state-centered surveillance.6 Both are premised on mistaken visions of total control.7 By avoiding the pitfalls of algorithmic overdetermination EU law should keep our future open in ways that empower us, instead of treating us as manipulatable pawns.



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