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:
- Clearly understanding the outcomes implementing AI will provide for their business;
- Focusing on an AI product’s capabilities instead of flashy marketing;
- Knowing when the technology is mature enough to mitigate risk;
- 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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