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Samenvatting AI & Society: Fixing Algorithmic Decision Making (S_AIS)
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AI & Society: Fixing Algorithmic Decision MakingElliot Ch. 1 – The complex systems of AI
AI currently and in the future addresses social, political, economical, and cultural processes that
include:
- AI within discrete apps, embedded within operating systems, and operating systems based
on AI
- Single-purpose robots throughout home and work life
- Bigger, faster, superdata analytics: ‘Colossal data’ (bigger big data) which will necessarily
involve new data curation and analysis approaches that enable more patterns from an ever-
diversifying range of media
- Low-power computational hardware, including neuromorphic computers that are more
suited to some applications of AI than traditional computers
- Miniaturized quantum encryption devices, which will underpin the security and trust that
will be required before new technologies are widely applied. This particularly applies to
applications with high-consequence failure modes (such as implants with direct access to the
brain)
- Advances in ML
- Advances in battery technology: enables stand-alone and mobile intelligence in a wide range
of applications
- Advances in machine cognition systems
- Mainstreaming of human-machine interfaces. This would enable a host of new applications,
the easiest to imagine being those using new brain-machine interfaces
- Massively parallel computational architectures and quantum computing
- Advances in generalized robotics, such as multipurpose labourer robots
- Advances in AI, such as the ability to mimic, and improve on, many aspects of human brain
function
You could say that AI is revolutionary for the world, after all, it changes and touches so many parts of
the world (from politics to technology). However, there is great uncertainty amongst people, maybe
due to the AI’s characteristic of invisibility.
AI could be defined as: “Technology with the ability to perform tasks that would otherwise require
human intelligence, such as visual perception, speech recognition, and language translation.” Note
that this is just one of the many possibilities to define AI. A key component that is missing in this
definition is the AI’s ability to learn from and adjust to newly given information stimuli.
Machine learning (ML) is one of the most important components of AI. After all, it tackles the bottle
neck problem for us. This concept is used to refer to the problem of distilling a lot of different
information (sources) to the key. ML is loosely structured in layers and sort of composed as a brain.
Deep learning refers to AI that deploys multiple layers of AI to solve complex problems and has
known an explosion of interest from businesses, media, and the finance sector.
Natural language processing (NLP) is another fundamental of AI and refers to all AI that is related to
the analysis, interpretation, and generation (of text- and speech-based) natural language. A good
example of this is Google Translate. We see a lot of this type of AI already and we’ll probably see a
lot more of this in the future. However, it is currently still unable to distinguish socially or culturally
damaging language.
Robotics has been characterized as the intelligent connection of perception to action in engineered
systems. It does not only include human-like robots but also that use cameras and sensors for
,example. Automotive and electronic sectors are currently the most invested in using automized
robots. It has changed and improved the efficiency significantly.
AI is interwoven with social systems and technological systems. The complex, overlapping
connections between technological and digital life can be analysed and critiqued from the following
sociological considerations:
1. There is the sheer scale of systems of digitization, of technological automation and of social
relations threaded through artificial intelligence
2. AI is not a new technology which simply transcends, or render redundant, previous
technologies. It depends on innovations that are thought of earlier in history
3. We need to recognize the global reach of AI as embedded in complex adaptive systems
4. There is the sheer omnipresence of AI. It can quickly do a lot of this at once on a global level
5. These systems which are ordering and reordering digital life are becoming more complex
and increasingly complicated
6. AI technologies go all the way down into the very fabric of lived experience and the textures
of human subjectivity, personal life and cultural identities
7. The technological changes stimulated by the advent of complex digital systems involve
processes of transformation of surveillance and power quite distinct from anything occurring
previously
There is of course critique on the extent to which AI can infiltrate our lives. We are shocked every
once in a while, like with Cambridge Analytica + Facebook in 2018. We then realize what AI is
capable of but after a while it dies down again.
Elliot Ch. 8 – Ethics of artificial intelligence
There are of course a lot of ethical concerns when it comes to AI, there have been attempts to create
some sort of authorities figure but do the newness and constant development of AI this had been
proven to be difficult. This article will discuss the main debates surrounding AI.
First, privacy. This debate is mainly structured around access to private data and data that is
personally identifiable. It is true that the technology has changed rapidly, and that the regulation
aspect has been left behind. The result is a certain anarchy that is exploited by the most powerful
players, sometimes in plain sight, sometimes in hiding.
AI creates the opportunity for data gathering as well as data analysis. Due to its online characteristic
it makes it difficult to regulate and it is often traded amongst one another (for free due to consumers
being unaware). After all, the main focus of social media, gaming, and most other sides of the
internet in this surveillance economy is to gain, maintain, and direct attention – and thus data
supply. Note also that AI is an important part of facial recognition software and thus another
economical way in which AI plays an important role.
Privacy-preserving techniques include:
- (Relative) anonymisation
- Access control
- And more
Differential privacy – include calibrated noise to output to establish some form of privacy.
Second, manipulation. AI discussions are about the accumulation of data, but they may very well
include the manipulation of the gathered data. Namely, AI can manipulate people into spending
, their money for example. Moreover, it can also be used for political propaganda with the help of
created videos or photos (e.g., Deep Fake).
Third, opacity (not being transcendent). AI systems are based on machine learning. They will provide
you with an answer based on their learnings. However, they will not be able to explain how they
came to that conclusion. This is difficult for people who are (most often) used to democratic
standards that allow us to make up our own minds.
Fourth, bias. Even though we often say that we want to eradicate bias, it is actually very necessary
for people to use biases in situations to help them determine what is the right way forward. AI does
have some form of bias but the wrong kind.
Fifth, deception and robots. Human Robot Interaction (HRI) is a very promising field in AI at the
moment. Of course, there are things that robots can't replace like care, love, and sex. On the other
hand, healthcare robots are far in their development and companionship/sex robots as well. The
latter will be hard to promote though due to humans’ attachment to other humans.
Sixth, autonomy and responsibility. Namely, who will be responsible to keep the AIs in check? Will an
autonomous vehicle be responsible for the crash, or will the driver/owner still be responsible?
Moreover, military robots can cause more war death because the face is taken away.
Seventh, singularity. People often have the thought that robots are made to take over the world.
This is the singular worldview that we currently have. It thus relies on the question, how can humans
stay in control over AI systems and/or superintelligence?
Eighth, machine ethics. Which will not be elaborated in this article.
Nineth, artificial moral agents. Should robots be given a legal status? Do they have rights? If yes, to
what extent do they have rights?
Broussard et al. (2019) – Artificial Intelligence and Journalism
There seems to be a hyperbole about technical tools where it is hyped to the extent that we need to
ask ourselves, will it really? According to the author of this article it relates to something that he calls
technochauvinism, or the assumption that technical solutions are always superior to other solutions.
We need to remember that AI is not a magic bullet.
Moreover, we see AI as a part of computer science and maybe mathematics. It is complicated and
full of algebra. However, this can partially be subscribed to people in the newsroom explaining it
poorly. They can only use and X number of words and thus forget to mention its benefits like
automation (Google Translate).
Humans also played into the hand of technology by brain drain from newsrooms and asking a lot of
money to work for a company (while AI is also very expensive, it came to a point where it is cheaper
than to hire a freelance journalist).
Others argue that we need to embrace what AI and humans can do together. For instance, if the two
work together the editing process will become more efficient. This is also called Human-Machine
Communication (HMC).
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