This
won’t go over well.
https://techcrunch.com/2024/05/30/misinformation-works-and-a-handful-of-social-supersharers-sent-80-of-it-in-2020/
Misinformation
works, and a handful of social ‘supersharers’ sent 80% of it in
2020
A
pair of studies published Thursday in the journal Science offers
evidence not only that misinformation on social media changes minds,
but that a small group of committed “supersharers,” predominately
older Republican women, were responsible for the vast
majority of the “fake news” in the period looked at.
Surveillance
from a drone you can see (or hear?) would be Okay?
https://pogowasright.org/the-alaska-supreme-court-takes-aerial-surveillances-threat-to-privacy-seriously-other-courts-should-too/
The
Alaska Supreme Court Takes Aerial Surveillance’s Threat to Privacy
Seriously, Other Courts Should Too
… In
arguing that Mr. McKelvey did not have a reasonable expectation of
privacy, the government raised various factors which have been used
to justify warrantless surveillance in other jurisdictions. These
included the ubiquity of small aircrafts flying overhead in Alaska;
the commercial availability of the camera and lens; the availability
of aerial footage of the land elsewhere; and the alleged unobtrusive
nature of the surveillance.
In
response, the Court divorced the ubiquity and availability of the
technology from whether people would reasonably expect the government
to use it to spy on them. The Court observed that the fact the
government spent resources to take photos demonstrates that whatever
available images were insufficient for law enforcement needs. Also,
the inability or unlikelihood the spying was detected adds to, not
detracts from, its pernicious nature because “if the surveillance
technique cannot be detected, then one can never fully protect
against being surveilled.”
Perspective.
https://www.schneier.com/blog/archives/2024/05/how-ai-will-change-democracy.html
How
AI Will Change Democracy
… In
particular, there are potential changes over four dimensions: Speed,
scale, scope and sophistication. The problem with AIs
trading stocks isn’t that they’re better than humans—it’s
that they’re faster. But computers are better at chess and Go
because they use more sophisticated strategies than humans. We’re
worried about AI-controlled social media accounts because they
operate on a superhuman scale.
It
gets interesting when changes in degree can become changes in kind.
High-speed trading is fundamentally different than regular human
trading. AIs have invented fundamentally new strategies in the game
of Go. Millions of AI-controlled social media accounts could
fundamentally change the nature of propaganda.
It’s
these sorts of changes and how AI will affect democracy that I want
to talk about.
AI
questions…
https://www.bespacific.com/stanford-hai-tests-westlaw-but-the-genai-results-look-worse/
Stanford
HAI Tests Westlaw But The GenAI Results Look Worse
Artificial
Lawyer:
“Ok this story is getting into unusual territory now. Artificial
Lawyer just got an email from the spokespeople for the Stanford
University HAI team
who told this site the researchers had updated their genAI study of
hallucinations in case law tools to include Thomson Reuters’
Westlaw. And guess what….? Westlaw has come out even worse than
the Practical Law tests (see below) according to what they have
published in an updated paper. Here is the new statement to AL from
HAI: ‘Letting you know that the research and blog post have been
updated with new findings. The
study now includes an analysis of Westlaw’s AI-Assisted Research
alongside Lexis+ AI and Ask Practical Law AI.’
They have updated the HAI group’s findings
here to
reflect this. As you may remember, this whole thing started when a
group of researchers tested whether LexisNexis’s and Thomson
Reuter’s genAI tools were as good as hoped for case law research.
There was plenty of confusion caused when the team tested Practical
Law, rather than Westlaw for the case law questions. They have since
been given access to Westlaw and hence the new results… Here is the
link to the original
story in Artificial Lawyer,
and there are two more articles with comments that follow it that
give more context – please see the AL site…”
The
answer?
https://www.technologyreview.com/2024/05/31/1093019/why-are-googles-ai-overviews-results-so-bad/
Why
Google’s AI Overviews gets things wrong
… Most
LLMs simply predict the next word (or token) in a sequence, which
makes them appear fluent but also leaves them prone to making things
up. They have no ground truth to rely on, but instead choose each
word purely on the basis of a statistical calculation. That leads to
hallucinations. It’s likely that the Gemini model in AI Overviews
gets around this by using an AI technique called retrieval-augmented
generation (RAG), which allows an LLM to check specific sources
outside of the data it’s been trained on, such as certain web
pages, says Chirag Shah, a professor at the University of Washington
who specializes in online search.
Once
a user enters a query, it’s checked against the documents that make
up the system’s information sources, and a response is generated.
Because the system is able to match the original query to specific
parts of web pages, it’s able to cite where it drew its answer
from—something normal LLMs cannot do.
One
major upside of RAG is that the responses it generates to a user’s
queries should be more up to date, more factually accurate, and more
relevant than those from a typical model that just generates an
answer based on its training data. The technique is often used to
try to prevent LLMs from hallucinating. (A Google spokesperson would
not confirm whether AI Overviews uses RAG.)
So
why does it return bad answers?
But
RAG is far from foolproof. In order for an LLM using RAG to come up
with a good answer, it has to both retrieve the information correctly
and generate the response correctly. A bad answer results when one
or both parts of the process fail.
And
thus ends the death watch…
https://www.bespacific.com/the-trump-manhattan-criminal-verdict/
The
Trump Manhattan Criminal Verdict
Via
Scott McFarlane – For the history books ===> Supreme
Court of the State of New York. The People of the State of New York
against Donald J. Trump, defendant
