I
might even read the whole book!
On
the path to AI
This
open access book explores machine learning and its impact on
how we make sense of the world. It does so by bringing together two
‘revolutions’ in a surprising analogy: the revolution of machine
learning, which has placed computing on the path to artificial
intelligence, and the revolution in thinking about the law that was
spurred by Oliver Wendell Holmes Jr in the last two decades of the
19th century. Holmes reconceived law as prophecy based on
experience, prefiguring the buzzwords of the machine learning
age—prediction based on datasets. On the path to AI introduces
readers to the key concepts of machine learning, discusses the
potential applications and limitations of predictions generated by
machines using data, and informs current debates amongst scholars,
lawyers and policy makers on how it should be used and regulated
wisely. Technologists will also find useful lessons learned from the
last 120 years of legal grappling with accountability,
explainability, and biased data.
I’ll
have to study this a bit...
How
to Design AI for Social Good: Seven Essential Factors
The
idea of artifcial intelligence for social good (henceforth AI4SG) is
gaining traction within information societies in general and the AI
community in particular. It has the potential to tackle social
problems through the development of AI-based solutions. Yet, to
date, there is only limited understanding of what makes AI socially
good in theory, what counts as AI4SG in practice, and how to
reproduce its initial successes in terms of policies. This article
addresses this gap by identifying seven ethical factors that are
essential for future AI4SG initiatives. The analysis is supported by
27 case examples of AI4SG projects. Some
of these factors are almost entirely novel to AI, while
the signifcance of other factors is heightened by the use of AI.
From each of these factors, corresponding best practices are
formulated which, subject to context and balance, may serve as
preliminary
...
To anticipate, these seven factors are: (1) falsifability and
incremental deployment; (2) safeguards against the manipulation of
predictors; (3) receiver-contextualised intervention; (4)
receiver-contextualised explanation and transparent purposes; (5)
privacy protection and data subject consent; (6) situational
fairness; and (7) human-friendly semanticisation.
Automating
lawyers.
Is
the Dawn of the Robot Lawyer upon us? The Fourth Industrial
Revolution and the Future of Lawyers
The practice
of law has been largely shielded from technological developments in
the course of the past 50 years. While the ways in which legal
professionals process and share information have evolved with new
technologies — primarily with the emergence of personal computers,
email and the internet — these technologies have not fundamentally
transformed it. However, if media reports are to be believed,
advances in technology in general — and the field known as
"Artificial Intelligence" (AI) in particular — are on
lawyers' doorsteps, and the
legal industry is on the cusp of radical change. Fuelled
by big data, increased computing power and more effective algorithms,
AI has the potential to fundamentally transform the way in which
legal work is done, the way in which law firms conduct business, and
the way in which lawyers deal with clients. A number of technologies
that fall under the AI umbrella, such as machine learning, natural
language processing, deep learning and others, have already brought
about the automation of many tasks that were, until recently,
performed exclusively by humans because they required human
intelligence. AI systems can also be used to perform many tasks that
lawyers routinely perform, such as contract analysis, case prediction
and e-discovery. And, according to proponents, these emerging
technologies can do it cheaper, faster and more efficiently. This
contribution examines the notion that recent advances in technology
will "disrupt" the legal profession. It first describes
the astonishing advances in technological progress, especially the
recent rise of AI. It then considers the technologies and areas of
legal practice most susceptible to this disruption. It concludes by
envisaging what AI might mean for the legal profession, and how
current technological trends might, in a relatively short period of
time, transform the way in which legal services are delivered.
For my
classes…
Dangers
of Bias in Data-Intensive Information Systems
Data-intensive
information systems (DIS) are pervasive and virtually affect people
in all walks of life. Artificial intelligence and machine learning
technologies are the backbone of DIS systems. Various types of
biases embedded into DIS systems have serious significance and
implications for individuals as well as the society at large. In
this paper, we discuss various types of bias—both human and
machine—and suggest ways to eliminate or minimize it. We also make
a case for digital ethics education and outline
ways to incorporate such education into computing curricula.
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