I wish them well.
https://www.databreaches.net/denver-suburb-wont-cough-up-millions-in-ransomware-attack-that-closed-city-hall/
Denver
suburb won’t cough up millions in ransomware attack that closed
city hall
John
Aguilar reports:
The
demand was big: $5 million to unlock Wheat Ridge’s municipal data
and computer systems seized by a shadowy overseas ransomware
operation.
The
response was defiant: We’ll keep our money and fix the mess you
made ourselves.
Read
more at The
Denver Post.
A very good ‘bad example.’
https://qmro.qmul.ac.uk/xmlui/handle/123456789/80559
Facial
Recognition Technology vs Privacy: The Case of Clearview AI
In January 2020, the New York Times revealed the
existence of Clearview AI, a company that had developed a facial
recognition tool of unprecedented performance. Various actors were
fast in declaring the loss of privacy accompanying the deployment of
the application. This paper analyses how the economic motives behind
facial recognition technologies challenge the established
understanding and purpose of the fundamental right to privacy by the
example of the EU. It argues that Clearview AI’s business model,
based on the surveillance of the company’s data subjects, forcibly
entails a violation of the latter’s fundamental right to privacy.
The traditional vertical application of fundamental rights in
cyberspace disregards the power asymmetry existing between private
individuals and private companies with state-like power in the
Digital Age, thus resulting in legal ineffectiveness in face of this
violation. The author
concludes that the most fruitful approach to safeguard privacy would
be the horizontal application of the fundamental right to privacy.
Humans need to talk ethics to their AI.
https://link.springer.com/article/10.1007/s43681-022-00214-z
Ethics in
human–AI teaming: principles and perspectives
Ethical considerations are the fabric of society,
and they foster cooperation, help, and sacrifice for the greater
good. Advances in AI create a greater need to examine ethical
considerations involving the development and implementation of such
systems. Integrating ethics into artificial intelligence-based
programs is crucial for preventing negative outcomes, such as privacy
breaches and biased decision making. Human–AI teaming (HAIT)
presents additional challenges, as the ethical principles and moral
theories that provide justification for them are not yet computable
by machines. To that effect, models of human judgments and decision
making, such as the agent-deed-consequence (ADC) model, will be
crucial to inform the ethical guidance functions in AI team mates and
to clarify how and why humans (dis)trust machines. The current paper
will examine the ADC model as it is applied to the context of HAIT,
and the challenges associated with the use of human-centric ethical
considerations when applied to an AI context.
Easily understood. Most “AI” is aimed at very
specific commercial goals, not broad ‘general intelligence’
issues.
https://www.zdnet.com/article/metas-ai-guru-lecun-most-of-todays-ai-approaches-will-never-lead-to-true-intelligence/
Meta's AI
guru LeCun: Most of today's AI approaches will never lead to true
intelligence
Yann
LeCun, chief
AI scientist of
Meta Properties, owner of Facebook, Instagram, and WhatsApp, is
likely to tick off a lot of people in his field.
With
the posting in June of a think piece on
the Open Review server,
LeCun offered a broad overview of an approach he thinks holds promise
for achieving human-level intelligence in machines.
Implied
if not articulated in the paper is the contention that most of
today's big projects in AI will never be able to reach that
human-level goal.
Interesting
(appropriate?) application of facial recognition. Protecting Taylor
Swift...
https://via.library.depaul.edu/cgi/viewcontent.cgi?article=4202&context=law-review
The
Legal and Ethical Considerations of Facial Recognition Technology in
the Business Sector
Anonymity
is no longer possible since most individuals have photo
identifications and social media posts with pictures available for
public viewing. Surveillance methods also continue to develop, which
has resulted in individuals being exposed to the greater use of
facial recognition techniques without their awareness or permission.
This system references equipment with the dual purpose of “connecting
faces to identities,” and permitting the “distribution of those
identities across computer networks.” The software is primarily
employed for “identification and access control or for identifying
individuals who are under surveillance.” This technology is
premised upon the idea that their inherent physical or behavioral
characteristics can be used to correctly recognize every individual.
Averaging ethics?
https://www.mdpi.com/2673-2688/3/3/45
Bridging
East-West Differences in Ethics Guidance for AI and Robotics
Societies of the East are often contrasted with
those of the West in their stances toward technology. This paper
explores these perceived differences in the context of international
ethics guidance for artificial intelligence (AI) and robotics. Japan
serves as an example of the East, while Europe and North America
serve as examples of the West. The
paper’s principal aim is to demonstrate that Western values
predominate in international ethics guidance and that Japanese values
serve as a much-needed corrective. We recommend a hybrid
approach that is more inclusive and truly ‘international’.
Following an introduction, the paper examines distinct stances toward
robots that emerged in the West and Japan, respectively, during the
aftermath of the Second World War, reflecting history and popular
culture, socio-economic conditions, and religious worldviews. It
shows how international ethics guidelines reflect these disparate
stances, drawing on a 2019 scoping review that examined 84
international AI ethics documents. These documents are heavily
skewed toward precautionary values associated with the West and cite
the optimistic values associated with Japan less frequently. Drawing
insights from Japan’s so-called ‘moonshot goals’, the paper
fleshes out Japanese values in greater detail and shows how to
incorporate them more effectively in international ethics guidelines
for AI and robotics.
(Related)
https://onlinelibrary.wiley.com/doi/full/10.1111/meta.12583
Flourishing
Ethics and identifying ethical values to instill into artificially
intelligent agents
The present paper uses a Flourishing Ethics
analysis to address the question of which ethical values and
principles should be “instilled” into artificially intelligent
agents. This is an urgent question that is still being asked seven
decades after philosopher/scientist Norbert Wiener first asked it.
An answer is developed by assuming that human flourishing is the
central ethical value, which other ethical values, and related
principles, can be used to defend and advance. The upshot is that
Flourishing Ethics can provide a common underlying ethical foundation
for a wide diversity of cultures and communities around the globe;
and the members of each
specific culture or community can add their own specific cultural
values—ones which they treasure, and which help them to make sense
of their moral lives.
Backgrounders…
https://www.taylorfrancis.com/chapters/edit/10.4324/9781003280392-13/data-privacy-artificial-intelligence-ai-lars-erik-casper-ferm-sara-quach-park-thaichon
Data
privacy and artificial intelligence (AI)
Artificial intelligence (AI) has disrupted the
ways customers and firms interact. However, AI runs on data and, in
the case of this chapter, customers’ personal informational data.
Yet, even in the face of a new paradigm for AI and customers’
online behaviors, there is a need for clarification of key concepts
and definitions in this domain. The main objective of this chapter
is threefold. First to provide a concrete definition of data privacy
which will conceptually drive this chapter. Second, we focus on the
three popular types of AI in the marketing domain AI types prevalent
(natural language processing, machine learning, and deep learning)
and identify how they give way to AI data privacy issues. Third,
this study will provide two case studies (Clearview AI and Hello
Barbie) which document and
explicate the means by which AI collects customer data and how this
gives way to data privacy issues. Overall, this chapter
will provide a conceptual alignment and understanding of the complex
arena of AI and data privacy.
(Related)
https://www.taylorfrancis.com/chapters/edit/10.4324/9781003280392-14/solutions-artificial-intelligence-ai-privacy-lars-erik-casper-ferm-park-thaichon-sara-quach
Solutions
to artificial intelligence (AI) and privacy
The main objective of this study is to understand
the implications of artificial intelligence (AI) and its influence on
data privacy. Via a series of case studies and discussions, this
chapter strives to provide insights into data privacy issues facing
marketers and customers in the digital space through their usage of
AI. To achieve this, this chapter will align and extend AI and data
privacy knowledge in two ways. First, by providing information on AI
types (natural language processing, machine learning, and deep
learning) and how/what customer data AI uses (e.g., segmentation and
targeting, personalization, and customer service) along with a
discussion of the accompanying arising data privacy issues. Then,
this chapter will provide potential solutions to the problems
presented and identified throughout this chapter (e.g., data value
propositions, degree of personalization, and federated learning).
The identified privacy issues and accompanying solutions within this
chapter will hopefully aid the understanding of current and future
marketing practitioners and academics in their use and understanding
of AI.
One of my favorite topics for (heated) debate.
(AI is only a tool?)
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4220854
Untangling
the Author/Inventor(Ship) Issues in the Artificial
Intelligence-Intellectual Output
The growing sophistication and diffusion of
Artificial Intelligence (AI) in creative tasks is triggering the
assumptions that the AI machine (rather than human) should be
considered as an author/inventor of the intellectual output produce
by or with the help of AI techniques. Due to this paradigm shift,
the orthodox conceptions of authorship and inventorship under
intellectual property (IP) regime are being challenged in ways that
have never been experienced before. Since the major area of existing
literature on IP policy has not examined the technological machinery
of AI system in depth, this study primarily investigates various
technical concepts and aspects behind the working mechanism of an AI
system. It provides a brief analysis of AI-human interaction in the
production process of AI-intellectual output (AIIO) and points out
that the human actor (designer, programmer, etc.) uses the AI system
as a problem-solving tool to produce desired intellectual output.
Furthermore, the study examines authorship and inventorship norms
under current IP realm and posits that only human actor should be
considered as author and inventor of the AIIO.
