Friday, June 07, 2019


Lawmakers can’t secure their campaigns because of the law? I think I’ll vote for someone who can figure out how to fix that problem.
Election Rules Are an Obstacle to Cybersecurity of Presidential Campaigns
One year out from the 2020 elections, presidential candidates face legal roadblocks to acquiring the tools and assistance necessary to defend against the cyberattacks and disinformation campaigns that plagued the 2016 presidential campaign.
Federal laws prohibit corporations from offering free or discounted cybersecurity services to federal candidates. The same law also blocks political parties from offering candidates cybersecurity assistance because it is considered an “in-kind donation.”




What if they get it wrong?
Amazon’s Home Surveillance Company Is Putting Suspected Petty Thieves in its Advertisements
Amazon's home surveillance company Ring is using video captured by its doorbell cameras in Facebook advertisements that ask users to identify and call the cops on a woman whom local police say is a suspected thief.
In the video, the woman’s face is clearly visible and there is no obvious criminal activity taking place. The Facebook post shows her passing between two cars. She pulls the door handle of one of the cars, but it is locked.
A post on the the Mountain View Police Department's websites details the incident and also shares an image from the Ring camera. "Footage obtained from a neighbor’s home captured a woman who is believed to be the suspect in the theft," the post says. The woman is suspected of stealing someone's purse and wallet from inside a car, and making a series of purchases around town with those stolen credit cards.
A spokesperson for MVPD told Motherboard in an email that "while we did not ask Ring to post footage, the additional outreach, and the additional eyes that may see this woman and recognize her, are most welcome and helpful!" A spokesperson for Ring told Motherboard in an email that its Facebook post encourages communities to work with local cops to "help keep neighborhoods safe."
Ring is also using the image of a woman who is innocent until proven guilty and calling her a thief in ad that it's paying to get in front of a targeted audience in order to sell more home surveillance equipment. The company doesn't claim to know for certain that she's committed a crime, and the police have yet to catch or convict anyone on this case.




I trust the police. Honest, I do!
iOS Shortcut for Recording the Police
"Hey Siri; I'm getting pulled over can be a shortcut:
Once the shortcut is installed and configured, you just have to say, for example, "Hey Siri, I'm getting pulled over." Then the program pauses music you may be playing, turns down the brightness on the iPhone, and turns on "do not disturb" mode.
It also sends a quick text to a predetermined contact to tell them you've been pulled over, and it starts recording using the iPhone's front-facing camera. Once you've stopped recording, it can text or email the video to a different predetermined contact and save it to Dropbox.




Definitely something to consider.
When AI Becomes an Everyday Technology
The evolution of AI has been a rich tale of exploration since its origins in the 1950’s, with the last decade providing an especially dramatic chapter of breakthrough innovations. But I believe the real story is what comes next — when the disruption stabilizes and machine learning transitions from a staple of Silicon Valley headlines to an everyday technology.
One of my favorite recent examples of this shift in possibilities comes from Carnegie Mellon University (CMU), where I formerly served as dean of the computer science department. While I was there, a student was considering her options for an upcoming artificial intelligence project, and thought of her sister, who happens to be deaf. She wanted to make it easier for her friends to learn the basics of American Sign Language, so she developed an AI-powered tool that tracked their movements and provided automatic feedback as they learned new signs. And here’s the best part: she wasn’t a computer science postdoc or even a grad student — she was a history major, taking an introductory class for fun.




"The first thing we do, let's replace all the lawyers with AI."
Artificial Intelligence and Legal Decision-Making: The Wide Open? Study on the Example of International Arbitration
Scherer, Maxi, Artificial Intelligence and Legal Decision-Making: The Wide Open? Study on the Example of International Arbitration (May 22, 2019). Queen Mary School of Law Legal Studies Research Paper No. 318/2019. Available at SSRN: https://ssrn.com/abstract=3392669
The paper explores the use of Artificial Intelligence (AI) in arbitral or judicial decision-making from a holistic point of view, exploring the technical aspects of AI, its practical limitations as well as its methodological and theoretical implications for decision-making as a whole.
The paper further finds that a blind deferential attitude towards algorithmic objectivity and infallibility is misplaced and that AI models might perpetuate existing biases. It discusses the need for reasoned decisions which is likely to be an important barrier for AI-based legal decision-making. Finally, looking at existing legal theories on judicial decision-making, the paper concludes that the use of AI and its reliance on probabilistic inferences could constitute a significant paradigm shift. In the view of the author, AI will no doubt fundamentally affect the legal profession, including judicial decision-making, but its implications need to be considered carefully.”




Well, I found it interesting… Would citing stick cases result in more wins?
Citation Stickiness
Bennardo, Kevin and Chew, Alexa, Citation Stickiness (April 19, 2019). 20 Journal of Appellate Practice & Process, Forthcoming. Available at SSRN: https://ssrn.com/abstract=3375050 – “This Article is an empirical study of what we call citation stickiness. A citation is sticky if it appears in one of the parties’ briefs and then again in the court’s opinion. Imagine that the parties use their briefs to toss citations in the court’s direction. Some of those citations stick and appear in the opinion — these are the sticky citations. Some of those citations don’t stick and are unmentioned by the court — these are the unsticky ones. Finally, some sources were never mentioned by the parties yet appear in the court’s opinion. These authorities are endogenous — they spring from the internal workings of the court itself. In a perfect adversarial world, the percentage of sticky citations in courts’ opinions would be something approaching 100%. The parties would discuss the relevant authorities in their briefs, and the court would rely on the same authorities in its decision-making. Spoiler alert: our adversarial world is imperfect. Endogenous citations abound in judicial opinions and parties’ briefs are brimming with unsticky citations.
So we crunched the numbers. We analyzed 325 cases in the federal courts of appeals. Of the 7552 cases cited in those opinions, more than half were never mentioned in the parties’ briefs. But there’s more — in the Article, you’ll learn how many of the 23,479 cases cited in the parties’ briefs were sticky and how many were unsticky. You’ll see the stickiness data sliced and diced in numerous ways: by circuit, by case topic, by an assortment of characteristics of the authoring judge. Read on!”




Even I can notice something strange when the two headlines are next to each other in my RSS feed. Is Step smarter than JPMorgan?
JPMorgan Scraps New App Service for Young People


(And)
Step raises $22.5M led by Stripe to build no-fee banking services for teens




Backgrounder… (Only two pages?)
Internet of Things – An Introduction
CRS Report via LC – Internet of Things (IoT): An Introduction, June 4, 2019 – “The Internet of Things (IoT) is a system of interrelated devices that are connected to a network and/or to each other, exchanging data without necessarily requiring human-to-machine interaction. In other words, IoT is a collection of electronic devices that can share information among themselves. Examples include smart factories, smart home devices, medical monitoring devices, wearable fitness trackers, smart city infrastructures, and vehicular telematics. Potential issues for Congress include regulation, digital privacy, and data security as discussed below.




Short of a full course, here are some tools for beginners, mid-level and advanced.
Student Resources for A.I. and Machine Learning Education
Hacker Noon offers a lovely breakdown of A.I. from a programmer’s perspective, including the industry’s “Holy Grail”: Artificial General Intelligence, or AGI (which some other resources call “General Artificial Intelligence”). KDNuggets also has a rundown of the basic terms and the technologies involved.
If you want to get to know some of the tools that actually make A.I. work, start off with Google’s three-hour introduction to deep-learning fundamentals. Since it’s Google, the materials inevitably focus on the company’s open-source software library, TensorFlow, that’s used in machine-learning applications (such as neural networks ).
Google also offers a machine-learning “crash course” with 25 lessons and 40+ exercises, designed to take roughly 15 hours to complete. You don’t need to know a lot to start off with it, but it’s definitely a smoother process if you have some knowledge of programming basics, Python, and intro-level Algebra.




Handy toolkit item?



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