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!
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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