We find ourselves at the dawn of what many believe to be a new era, one in which artificial intelligence promises to drive cars, promulgate juridical legislation, and offer medical diagnoses. I am going to focus on the last point mentioned, trying to offer a point of view for a horizon that is not as far as some skeptics may believe. The world stutters and questions itself on what even the brightest and most eccentric figures have had on mind for quite some time already. It is the one query that has obsessed the tech sector, shaking its steel foundation, which can be phrased like: “Is Generative AI (A.G.I) the revolution supposed to save society or the one that will doom it?”. The answer lies in its potential as well as in its capability to drastically change the everyday: a new era of capitalism awaits, or as Giovanna Melandri, ex Italian Minister, recently put it during the Impact Now convention, “Another form of capitalism is possible”.
The mounting anxiety about A.I isn’t because of some boring applications constantly fed to users, neither the ones that perform basic tasks, such as completing text messages or moving unwanted e-mails into the junk. “It is the rise of A.G.I that worries the experts” (Morozov, E., 2023), because of the rapid progress made into the fields as well as the enormous market cap it offers to organizations. What needs to be cleared before getting dirty on health corporates, is what concerns most scientists and venture capitalists, as well as most of highly institutionalized officials and government functionaries. Generative Artificial Intelligence is the progressive sister of A.I, “Generative AI can be thought of as a machine-learning model that is trained to create new data, rather than making a prediction about a specific dataset” (Zewe, A., 2023). What comes to mind after reading that is Terminator alike scenarios, the rise of machines and consequent annihilation of the human race, or Matrix indeed, where Synthients dictates both society and the world population.
I recently participated at a seminar where Angelo Buscema, Judge for the Constitutional Court of Italy, mentioned that AI would had never been able to replicate the creativity trait that is commonly referred to as one of the many humans’ constituents. I then proceeded to follow the end of one eternal lecture on why human race couldn’t possibly be imitated, surely not by “some emotionless piece of junk”, and to the high-profile figures present in the room, to those dinosaurs I said, “There is a funny scene in I, Robot and it goes something like: ‘Can a robot write a symphony? Can a robot turn a canvas into a beautiful masterpiece?’ Will Smith asks, ‘Can you?’ the Robot goes”. I could feel President Buscema smirking away, without even looking at his face; silence seemed ambiguous, just for a moment, before being swiped away by a light sense of approval. Frames like these make me smile but also worry me. There
no space for sterile oppositions in this world, and it is imperative this field is to be protected from it, otherwise it would be decaying before it even reached its full potential.
Discussion of A.G.I are rife with rhetoric confrontations and apocalyptic scenarios, yet it is starting to convince more and more academics as well as investors. “Mr. Altman, the face of this campaign, embarked on a global tour to charm lawmakers” (Morozov, E., 2023), which eventually led Mr. Musk to put up a scene where he accuses Altman and OpenAI to have turned the once born no profit organization into a money seeker machine.
Generative AI usage is already showing some of its potential across several industries: financial giant “Morgan Stanley is testing the technology to help its financial advisers on a better leverage insight from the firm’s over 100,000 research reports. Iceland’s government has partnered with OpenAI to preserve the endangered Icelandic language.” (www.mckinsey.com., n.d.). The revolution that we are experiencing is going to be the new look for the imminent future, one that is just across the room, behind the door, waiting to be brought to light.
With the groundbreaking emergence of generative artificial intelligence, the self-reliance on informal sources has been attracting both patients as wells as physicians and health care providers: the first for self- reassurance, the rest as a tool that can accompany work decisions, either by influencing them or just by providing useful notions, with considerate time savings. Health corporates envisions a new future for medicine, one where doctors won’t be using fax taxes to send and receive information from other
is
hospitals anymore, one where X-rays are scanned faster, with a better pattern recognition, which is something that even the best doctors would be less adept to decipher, compared to a machine.
industry as a front-runner beneficiary: algorithms are getting more relying, precise, which allowed more
Artificial
Intelligence had already started to gear-up its application in several sectors, with the pharmaceutical
researchers and doctors to assist the decision-making process. A.G.I can determine the right therapy for
any patient, including a personalized medicinal assistance, which can facilitate the application in cancer
treatment, for example: bloods and tissue can now be divided into samples, which may include both
healthy and cancer cells, these samples are later exposed to a various cocktail of drugs. Then using
computer vision (machine-learning models trained to identify small changes in cells) instead of putting a
patient through multiple months-long courses of chemotherapy, which can be highly harmful and
counterproductive, dozens of treatments all at the same time are to be tested; this method delivers high
efficacy in finding the right drug ought to eliminate the cancer cells.
Processes like these further help managing the clinical data generated, which can be used for future drug development. Even though AI is years from developing its own drug (and surely not because technology isn’t yet up to task) the pharmaceutical industry is pushing for the whole process to be accelerated, trying to gain the upper hand on something that can revolutionize the whole sector. What makes A.G.I unique to the drug development sector, is its access to new biology, an improved chemistry structure, a better success rates, and most importantly a quicker and cheaper discovery processes. A better success rates leads to higher incentive for trusting the algorithms, which automatically translate into more profit, as people that were once skeptical, now recognize the value behind it.
Steps are being taken meticulously by major actors: “Alphabet recently launched Isomorphic Labs based on AI breakthroughs at its DeepMind AI operation, Nvidia has invested in the Clara suite of AI tools and applications, and Baidu’s AI drug discovery unit has struck a major deal with Sanofi” (Ayers, M., et al., 2022).
As generative AI is gradually taken off and its deployment gets under way, corporations need to reevaluate the global chain that they once applied to traditional artificial intelligence models. First, the technology required is way more complex than previous models, which translates into bigger initial investments, that could prevent smaller health corporates to enter the market and develop what is it needed to stay competitive.
Many areas will still be controlled by tech giants, because many already have the technological assets necessary to gain control of this new revolutionary branch of AI, but researchers suggest that companies that utilize unique, specific data, to improve their application can gain a notable competitive edge compared to those who don’t. This means that even if the competition may already be unbiased, even from the beginning, the hegemony will be won by those who have access to insights or information that competitors lack. Data are the new currency.
Investments flow like rusty paper on a windy night, but while news like these set an unprecedent record, they also pave the way for potentially dangerous scenarios: where private giants, by financing health conglomerates, dictates decisions that should be made by whole nations, and surely not by few megalomaniacs. Such decisions may concern who get the drugs and at what price, entire nations could be left hanging just because they can’t afford them; but then again, we are quite familiar with scenarios like the one described. Just at the end of 2021 (right in the middle of the COVID-19 pandemic) “only 2.5% of the 6.4 billion vaccine doses administered globally had been in given to Africa, compared to the 60% of the population in advanced economies that were fully vaccinated” (World Economic Forum., n.d.). Despite ad hoc regulations can prevent situations like this to happen, which would require the collaboration of people with several different backgrounds, spacing from engineering to ethics, the main issue regarding artificial intelligence (which has only been incentivized by generative ai) are biases.
Is it just me, or what I find concerning about artificial intelligence is the fact that it learns from human, which have a history of making the wrong kind of decisions.
“73% of senior IT leaders are concerned about biases outcomes” (Baxter, K. and Schlesinger, Y., 2023), but what are exactly biases in healthcare?
According to the National Healthcare and Disparities, a report dated 2019, White patients were “more likely to receive better quality care” (www.medicalnewstoday.com., 2021) than other minority groups, including Black or Hispanic patients. But this has nothing to do with A.G.I, that is our world works: minorities have harder time accessing healthcare systems and women potentially face easier dismissal because their chronic pain is often confused as “emotional, hysterical and sensitive” (www.medicalnewstoday.com., 2021). But the list goes on, as a study from 2019 cites, 80% of medical students have an “implicit bias against lesbian and gay people” (Morris, M., et al., (2019)). Since generative AI algorithms learn from real events and actual cases that are being fed to it, it is clear how such biases could influence and target specific categories, consequently forcing on decisions that otherwise would have not been taken.
Society acts so outraged, because of those prejudices, but forgets the fault it carries, and the pivotal role it has had in making so many choices that had contributed to accentuate behaviors which cannot be tolerated.
One side has not yet been discussed, the one that is strictly involved with the law perhaps. Since there is no regulation yet, concern about accountability grows stronger: legal liability makes someone be accounted for, or as the law cites “A party can be held liable based on their own actions, their own inactions, or the actions of people/animals for which they are legally responsible” (LII / Legal Information Institute., n.d.). Which should put an end to the discussion, shouldn’t it? Right, but let’s say a drug prescribed by A.G.I accidentally kills a patient, should the doctor that trusted the machine be held responsible, or should it be the technician that developed the program instead? Should it also be the company that hired the software developer? In that case, just the project manager or all the way to top management? This can result in legal disputes, that can severely damage both the financial and reputational side of the corporation.
Additionally, in the absence of stricter regulations, certain entities may end up dominating the market, leading to a concentration in the sphere of influence which, as we said, can harm innovation and reduce access for those smaller players involved. The consequently economic disparities would only exacerbate
existing inequalities, setting new ways of discomfort and a decline in trust, which is the one thing that this field requires, the utmost confidence from society.
As the digital landscape continues to evolve, harnessing the power of Generative AI will be imperative for health corporates to thrive in an era defined by complexity, innovation, and rapid technological change. Embracing A.G.I is revolutionary and certain companies would surely get richer from its worldwide applications, but extra attention will need to be applied though, as the possibility for potential biases, both social and economic, is behind every corner.
One thought is left to the reader, what is it that makes us so afraid of changes? Is it the literature that has been fed to us? Is it because we have seen “2001: A Space Odyssey” too many times? Or is it because we don’t want to admit that a sick patient puts more money into the pocket of those health giants, rather than a healthy one? as ex Italian Minister of Health Rosy Bindi once said.
Articolo a cura di Massimiliano Marzocchi