The biggest problem
with artificial
intelligence (AI) is that
most people
have heard of it,
but they
have no idea what
it actually means. As a result, the “average” member of the
public hardly ever uses AI tools in his or
her everyday activities.
The term “artificial intelligence” was actually coined back in
1956, while the term “machine learning” was first mentioned in 1959 (see Picture
1 below).
For the time being, the
term “artificial intelligence” implies making use of very good,
useful, self-adjusting algorithms that work well when processing large sets of available
data and information.
However, “artificial
intelligence” is definitely not
about intelligence.
This is because intelligence implies the ability to invent new things
and generate new information.
Right now only the human brain is capable of inventing new
things and generating new information.
And scientists still have only sketchy knowledge about the way our human
brain functions: it is made up of at least 85 billion nerve cells or neurons,
along with thousands of other types of cells. As the New York Times put it:
“Researchers identified some 3,300 types of brain cells, an order of magnitude
more than was previously known, and have only a dim notion of what most of them
do” (see Reference 1 and Picture 2 below).
And you cannot
reproduce any “artificial” brain unless you know exactly how the “natural”
brain works.
The chances that
our understanding
of how the human
brain works will increase significantly
in the near future
are very low.
Therefore,
there are no chances that very good,
useful, and self-adjusting algorithms
will be transformed into something similar
to human
consciousness (aka “artificial general intelligence”)
in the foreseeable future.
Because we still do not know what is
the essence of human consciousness.
I
do not rely on ChatGPT because it
is like relying on
everything that is posted on the web, while AI-generated texts
are easily recognized because they sound
artificial and “plastic”
like modern
pop music.
I
do not use personalized content recommendations and suggestions because they
are repetitive, unimaginative, and predictable by relying on my searches in the
past rather than on my current interests.
I
do not rely on
Wikipedia articles because they
should be checked and re-checked by reading scholarly and academic sources. For
the same reason I do not rely on Hollywood
movies or Netflix series to get an idea about
various historical events because this is the best way to be
misinformed.
I do not use smart TVs, refrigerators, vacuum cleaners,
or voice assistants because they would make my life just marginally more
comfortable, while being useless overall.
I use machine translation. It
is definitely useful because it is fast. But its quality is still so low and
often misleading in contrast to professional human translation that it needs to
be manually reviewed and corrected. It is like providing first aid by a
stranger before seeing a real doctor.
As Euromonitor International
put it, “Last year, Ask AI was all about ongoing experimentation and shifting
expectations of generative AI solutions. Increased adoption also raised skepticism
as consumers pointed to flaws in output, leading to the AI Ambivalent trend for
2025” (see Reference 2 below).
Many investors agree. As the
Reuters news agency has recently reported, “European companies that are
spending big on generative artificial intelligence need to start showing
returns on their massive outlays by next year, or risk investors losing
patience after they paid sky-high prices to join the market boom” (see
Reference 3 below).
Such skepticism is perfectly
acceptable when you deal with any new, untested technology because there is no
guarantee that this new, untested technology will go mainstream or even become
dominant in the future.
The thing is that the amount
of investments in the area of artificial intelligence has already exceeded $1
trillion. Another $500 billion is
expected to be invested in the United States alone (see Picture 3 below).
I would assume that is enough money to hire a person who would be able to compile a
list of
practical AI applications on a single A4 sheet
to explain
where artificial
intelligence is being used now in addition to being useful,
fast-working, self-adjusting algorithms when
processing large sets of available information. And, most importantly, how AI tools can be used
by ordinary people in their daily lives today.
The Business Insider reported
that “OpenAI aired its first-ever Super Bowl ad on Sunday, making a $14 million
statement that artificial intelligence belongs in the same category as fire,
the wheel, and the internet” (see Reference 4 and Picture 4 below).
If I lose access to electricity, running water,
Internet connections, the ability to travel by car, buy a medicine, have a CT
or MRI scan, it will be a disaster.
If the existing version of “artificial
intelligence” fails or disappears altogether what is going to happen?
Or is it just one of those potentially
breakthrough technologies, like nuclear fusion, a cure for cancer, quantum
computing, or interplanetary travel where further progress has been either painstakingly
slow or has stalled altogether since the 1960s and 1970s?
The most reliable and satisfying life strategy is
achieving results that exceed initial
expectations. The initial expectations
with respect to artificial intelligence are so high and uncertain at the same time that it is all becoming increasingly
disturbing.
References:
1. “The
Human Brain Has a Dizzying Array of Mystery Cells”, Carl Zimmer, The New York
Times, October 12, 2023.
2. “What Are the Top Consumer Trends in
2025?”, Alison Angus, Euromonitor International, January 23, 2025.
3. “European
Investors Say Clock Is Ticking for AI Adopters to Deliver”, Lucy Raitano,
Reuters, March 26, 2025.
4.
“OpenAI
Compares ChatGPT to Humankind’s Greatest Inventions in Its First-Ever Super
Bowl Ad”, Effie Webb, The Business Insider, February 10, 2025.
