An
opportunity to remove these “Forrest Gumps” from the gene pool?
Cell-tower
attacks by idiots who claim 5G spreads COVID-19 reportedly hit US
The
Department of Homeland Security is reportedly issuing alerts to
wireless telecom providers and law enforcement agencies about
potential attacks on cell towers and telecommunications workers by
5G/coronavirus conspiracy theorists. The DHS warned that there have
already been "arson and physical attacks against cell towers in
several US states."
The
preposterous
claim that
5G can spread
the coronavirus,
either by suppressing the immune system or by directly transmitting
the virus over radio waves, led to dozens of tower
burnings in the UK and mainland Europe.
(Related)
We can only hope.
Perspective
and Infographic.
What’s
Old Is New Again: Examining Privacy Enhancing Technologies
The
term Privacy Enhancing Technologies (PETs) has been around for
decades and is now experiencing a renaissance as the global
awareness, demand, and regulation for privacy increases. While the
label itself is intuitively powerful — who isn’t in favor of
technologies that enhance privacy? — it is also ill-defined and
often misunderstood.
… To
unpack what this means, it’s helpful to consider the three states
of data — at rest, in transit, and in use — which can represent
the three segments of the Data
Security Triad.
Oh
what an expensive web we weave when first we practice to deceive.
Volkswagen
loses landmark German 'dieselgate' case
Germany's
highest civil court has ruled that Volkswagen must pay compensation
to a motorist who had bought one of its diesel minivans fitted with
emissions-cheating software.
The
ruling sets a benchmark for about 60,000 other cases in Germany.
The
plaintiff, Herbert Gilbert, will be partially reimbursed for his
vehicle, with depreciation taken into account.
VW
said it will now offer affected motorists a one-off payment, and the
amount will depend on individual cases.
The
company has already settled a separate €830m (£743m) class action
suit involving 235,000 German car owners.
It
has paid out more than €30bn in fines, compensation and buyback
schemes worldwide since the scandal first broke in 2015.
I think they
have the main roles correct.
The
Six Roles You Need on Your AI Team
Let’s say
you were already sold on AI: You’ve gotten yourself and your
executive team trained on the basics of AI; you’ve studied use
cases; prioritised the business pain points that could align with AI
solutions; and allocated funding to launch a few pilots.
… So, if
you’re ready to start assembling your cast of AI characters, who do
you need? What skillsets should you look for to build your
enterprise’s AI efforts?
Here are the
six roles you need on your AI team:
The strategist
The data engineer
The data modeller
The data in production person
The infrastructure and scale builder
The data analyst/visualiser
(Related) A
prelude to AI.
A
Philosophy of Data
We argue that
while this discourse on data ethics is of critical importance, it is
missing one fundamental point: If more and more efforts in business,
government, science, and our daily lives are data-driven, we should
pay more attention to what exactly we are driven by. Therefore, we
need more debate on what fundamental properties constitute data.
In the first section of the paper, we work from the fundamental
properties necessary for statistical computation to a definition of
statistical data. We define a statistical datum as the coming
together of substantive and numerical properties and differentiate
between qualitative and quantitative data. Subsequently, we qualify
our definition by arguing that for data to be practically useful, it
needs to be commensurable in a manner that reveals meaningful
differences that allow for the generation of relevant insights
through statistical methodologies. In the second section, we focus
on what our conception of data can contribute to the discourse on
data ethics and beyond. First, we hold that the need for useful data
to be commensurable rules out an understanding of properties as
fundamentally unique or equal. Second, we argue that practical
concerns lead us to increasingly standardize how we operationalize a
substantive property; in other words, how we formalize the
relationship between the substantive and numerical properties of
data. Thereby, we also standardize the interpretation of a property.
With our increasing reliance on data and data technologies, these
two characteristics of data affect our collective conception of
reality. Statistical data's exclusion of the fundamentally unique
and equal influences our perspective on the world, and the
standardization of substantive properties can be viewed as profound
ontological practice, entrenching ever more pervasive interpretations
of phenomena in our everyday lives.
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