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The advance of AI and its increasing capacity to perform
work with a creativity indistinguishable from humans is fuelling more
discussion and some concern.
At the Venice Biennale running now until July, visitors can
see an “ultra-realistic humanoid robot artist,” called Ai-Da. She’s been
trotted out for a few years now and this time is showcasing paintings performed
by her AI and made by her robotic hand.
Its British inventors have moved beyond the question
‘whether or not robots can make art?’ to exploring ‘now that robots can make
art, do we really want them to?’
Soon, AI algorithms “are going to know you better than you
do,” warns Ai-Da’s co-inventor Aidan Meller in The Guardian. “We are
entering a world not understanding which is human and which is machine.”
Going further, he implies that society could be edging away
from humanism, into an era where machines and algorithms influence our
behaviour to a point where our “agency” isn’t just our own.
“It is starting to get outsourced to the decisions and
suggestions of algorithms, and complete human autonomy starts to look less
robust. Ai-Da creates art, because art no longer has to be restrained by the
requirement of human agency alone.”
Art or beauty as they say is in the eye of the beholder so
if a machine creates art and we accept that then it is art.
This is what researchers Leah Henrickson and Simone
Natale have termed the “Lovelace Effect“ (named after the 19th century
female mathematician who essentially programmed Charles Babbage’s first
computer for him and whose Christian name is not coincidentally, Ada).
The Lovelace effect shifts the focus from the technological
capabilities of machines to the reactions and perceptions of those machines by
humans.
“How, where and why we interact with a technology; how we
talk about that technology; and where we feel that technology fits in our
personal and cultural contexts,” all has a baring on whether what we see or
hear is called art, Natale and Henrickson say.
AI in the workplace
That all our jobs are in danger of being replaced by AI is
presented as a certainty by AI expert Kai-Fu Lee. In his new book AI
2041 he predicts that all blue-collar and all white-collar work jobs
will be phased out of existence as AI proves it can do those jobs better – and
cheaper.
Moreover, any craft-related jobs that require dexterity and
a high level of hand-eye coordination will also eventually been taken over by
AI by 2041. That would include many areas of post production such as VFX,
animation and assembly edits. Even programme direction of as-live sports matches
could be done by a bot.
“Engineering is largely cerebral and somewhat creative work
that requires analytical skills and deep understanding of problems,” Lee
told IEEE Spectrum. “And those are generally hard for AI. But if you’re a
software engineer and most of your job is looking for pieces of code and
copy-pasting them together—those jobs are in danger.”
In order to adjust to the digital AI era we are urged to
understand the basic tenets of coding, programming languages, scripts,
algorithms, compiling, and machine language by US academics Paul Leonardi and
Tsedal Neeley.
Developing a digital mind
In their new book The Digital Mindset: What It Really
Takes to Thrive in the Age of Data, Algorithms, and AI, they argue that
lacking this basic digital awareness would make it difficult to participate in
the digital economy.
Critically this mindset requires a shift in how we think
about our relationship to machines. We shouldn’t anthropomorphise AIs but treat
them exactly as what they are – machines which are built with human input and
embedded with human bias.
“Even as they become more ‘humanish’, we need to think about
them as machines,” they write.
They point out that advances in AI are moving our
interaction with digital tools to more natural-feeling and human-like
interactions. For instance, conversational user interfaces like Hello Alexa or
OK Google give us the ability to act with digital tools through writing or
talking that’s much more the way we interact with other people.
The problem is that these AIs aren’t quite up to human
mental agility or mimicry yet.
“We are still some ways away from effective human-like
interaction with the technology,” say the professors.
But it seems inevitable that AI will catch-up, not least because
we’re feeding it on the neural networks with which our own brains work.
Does that mean AI ultimately attains consciousness?
Graz University’s Wolfgang Maass has hinted at such,
saying future neuromorphic setups may one day begin to explore how the
multitude of neuronal firing patterns work together to produce
consciousness.
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