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The end is clearer than the beginning
Talking (and walking) about what comes next - Media Ecology Newsletter #13
The end is clear, the new beginning is not, yet.
In this issue of the newsletter, I report on some of Jessica Powell's thoughts about Silicon Valley companies, I comment on a Nature article on the relationship between science and technology, and I report on the results of a major OECD conference on artificial intelligence design.
What do these topics have in common?
I am working to expand a paper to be published by Springer on the relationship between future and harmony. This is a topic started at Entopan with a book on the notion of “harmonic innovation” written by Francesco Cicione, with my collaboration and with contributions by a number of important thinkers. The book that I’m writing, as the paper from which it comes from, will be about the very ambiguous and deeply generative concept of "harmonic future.”
It will not be an easy task.
If it is clear that we have concluded a neoliberal historical phase, it is also clear that there is no shared project to start a new historical phase.
The long goodbye to the single way of thinking that has guided the West since the end of the 1970s and that has been undermined by the many crises of the new millennium is a never-ending story. Financial markets don't stop producing avalanches of money, people don't stop distrusting states, and taxes don't stop being used to finance big private traditional businesses when they are in crisis.
At the same time, we cannot fail to see how many things are changing: sensitivity to an innovative interpretation of sustainability is much more widespread than it used to be, many companies are setting themselves social value objectives, the modernization of the media is in turn generating far-reaching changes at all levels of culture, economy and society, opening up possibilities that were previously unthinkable.
A new narrative is emerging. A narrative that speaks of ecology and innovation, diversity and authenticity, science and society. This is very good. But a narrative must not be left alone. Facts matter.
What has really ended? What has begun? Answers are not easily found. But listening to people who have delved into the topic can help. And the privilege of journalists is to listen to people like that and report what they say.
on the next style for innovative companies: diversity, authenticity, quality
I’ve been talking by phone with Jessica Powell author of “The Big Disruption”, former vice president of communications at Google and a Stanford alumna. Her book has just been translated into Italian and I wrote about it on Il Sole 24 Ore. The book is meant to be, as the subtitle says, “A Totally Fictional But Essentially True Silicon Valley Story”.
In Powell's book, which presents itself as a satire, a company of engineers totally lacking in understanding for emotions and the quality of human relationships tries, among other things, to program an app that can improve the chances of "nerds" to be liked by girls. Needless to say, the first version is a disaster for the productivity of the engineers who allow themselves to be drawn into endless amorous conversations. From version to version, the designers will transform the application into a system that provides a balance between the engineers' productivity and their ability to find an emotional satisfaction of a sort that is less disruptive and more instrumental than love. The engineers attempt to build a utopia, but only succeed in creating a more efficient software factory and a more powerful company. And an even more unscrupulous kind of company. Ready to grow even more. Much more.
While the book is clearly witty and entertaining, the back of the book is even more interestingly debatable. Basically, Jessica Powell seems to think that the outcomes of Silicon Valley companies can't be much different than what their fundamentally male, white, wealthy "anthropology" allows them to think. Giants like those that dominate Silicon Valley and the world are now unreformable. To change the world it is not enough to say you want to do it, you must first change the organization of the companies that should innovate.
She has started a new company called Audioshake to help musicians make the most of their artistic work. And what's so special about it? Interviewing her reveals a notable difference. "We don't want to grow," says Powell, co-founder of Audioshake. "Our company is different. We want something small. That really helps musicians, one by one. I want to get to know all the people who work with us. I want to think about the needs of women right from the start. Not as a later adjustment. I want to hire diverse people from the beginning, otherwise it's hard to change direction afterwards. The value of small is to be reevaluated." Will it become a new paradigm? "Finance at a huge power. I'm skeptical. But I like to think that a new balance can be reached. From Europe we can learn. Not so much to make technology. But in building more sober corporate cultures. It's not for nothing that the idea for the book was born in Europe." After centuries of Europe destroying the world and itself, it has now arrived to build an image of wisdom. In the hope that it can go beyond the image.
Jessica Powell, The Big Disruption. A Totally Fictional But Essentially True Silicon Valley Story, published on Medium. Jessica’s book’s site. Jessica’s column for the New York Times. Audioshake.
on the relationships between science and technology: empirical, social, diverse.
On January 29, 2021, around 11:30 am, I had the honor of participating in the Radio3 Science program, hosted by Elisabetta Tola. Theme: the relationship between technology and science. Cue: a magnificent piece in Nature that recalled the great softwares that in the last seventy years have enabled an acceleration of the scientific use of computers (Nature, Ten computer codes that transformed science). Starting with the 1957 "Formula Translation," Fortran.
In the speed of statements to be made in a radio broadcast, albeit with the help of a highly competent presenter, topics remain in mind that have not passed with due problematicity. And in a subject as complex as this all the more so. So I report here the notes I took in response to Elisabetta. Just to have a reminder.
The relationship between technology and science
1. Technology has always enabled scientific discovery or served to prove theories. Galileo's ideas are remembered, but his telescope should never be underestimated.
2. It is clear that computers have made it possible to do scientific work that was previously unthinkable: computer images and neuroscience, genetic databases and biology, molecular simulations and understanding the characteristics of new nanomaterials, big data and artificial intelligence.
3. The growth of computer contribution to science is obviously driven by several dynamics: a. Moore's law (a computer at the time of the moon landing could do 100 thousand operations per second, as many as a remote control does today; a smartphone today does 10 billion operations per second; a miniature supercomputer installed on a Google autonomous car in Phoenix, designed by Eurotech, does 100 trillion operations per second); b. The improvement of the interface that made possible for those who were not "computer scientists" but were scientists tout court the use of computers; c. The growth of software for computing, for storage and exchange of information in the community of scientists, for image recognition, for databases, for simulations.
4. Digital technology has a particularly profound ability to address science beyond the single function, because it suggests terrain and avenues of research that were not possible without it. It also suggests innovative epistemological approaches, however debatable: in a context with a large amount of data and systems for recognizing patterns of behavior of phenomena, one can imagine a kind of reconfiguration of the function of theory, which is no longer just the idea - to be verified - that a model corresponds to reality, but becomes above all the source of the formulation of questions to be asked to models, to emerging regularities and above all to unexpected irregularities. (Warning. The possibility of studying emerging regularities from large amounts of data has also suggested to someone the trivializing idea of the "end of theory": according to this idea, there is no need to theorize, it is enough to look at the data; as if looking at the data, choosing what they say, asking questions to the data, learning to compare what the data say about a certain reality with what one thought about that reality, and so on, did not need theory; this is a thought that may be fine for promoting a magazine but not for advancing knowledge - Wired).
5. But the logic of technology can also influence science in an economically dangerous way. If one considers the technology produced privately by for-profit companies that protect their knowledge with trade secrets and patents, or copyrights, it may be that science is led to do the same, sharing less and keeping more in the secrecy of laboratories, in order to maximize revenue. This would be a betrayal of the fundamental idea of science, which is founded on the sharing of knowledge generated by a common set of epistemologies in a community of scientists. Not all technology is closed, of course. There is open source technology, information in creative commons, the set of solutions openly available to anyone who wants to use them. That technology does not lead scientists into temptation. But certainly, a sort of science that keeps knowledge secret is not science.
Digital technology has accelerated innovation by overwhelming entire industries over the past thirty years. But by accelerating science, too, it has generated an acceleration of acceleration. Nano, bio, and neuro sciences, along with information sciences, now do things unthinkable without computers. The same can be said of astronomical research, particle physics, chemistry, and so on. But one fact is important: science is not technology. The conceptual separation between the two dimensions of knowledge is crucial.
In this regard, Naomi Oreskesshould be read. In her very profound analysis, there is no single scientific method: there is a community of people who make decisions about the soundness of scientific ideas based on empirical and social operations. In this community, diversity is essential to the quality of the results.
Luca De Biase - Scienza e tecnologia. Appunti per Radio3 Scienza
on A.I. and jobs: technology can only be as human as its designers are able to be
The week of in-depth analysis organized by the OECD around the social consequences of artificial intelligence that has just ended marked a new turning point in the spirit with which this technology is evaluated. Over time, we have gone from uncritical enthusiasm, when the economic importance of big data became apparent and artificial intelligence was seen as the right technology to exploit it, to discouragement, when we saw that nothing of what the data and algorithms said was as objective as we had naively hoped. And indeed it had heavy consequences.
In the period of enthusiasm, people dreamed of the immediate advent of driverless cars, personalized marketing, and more documented credit ratings. In the period of pessimism, problems were denounced. Propublica discovered that the programs adopted by American police were rife with racial bias. The British government was getting the software wrong for selecting students who deserved to enter college. Scholars at universities like Oxford calculated that 47% of jobs would be replaced by artificial intelligence. As research has matured, it has become clear that uncritical enthusiasm and outright pessimism are wrong.
Today we look at the phenomenon with more balance.Stefano Scarpetta, of the OECD, has long shown that a share of around 14% of jobs will disappear. But a double quota of jobs will undergo strong adjustments. In all cases, it will be necessary to prepare the population for change, increase investment in education, and manage the transformation with anticipation and vision.
David Autor, of MIT, at the OECD megaconference, noted that we need to approach the issue by accepting its complexity. "We thought machine learning only worked for specialized applications, but we were surprised to find that it is very adaptable. Which can generate major transformational leaps. There will also be societal effects: with increased inequality and thus a slowdown in growth." For Autor: "Everything must be done to improve people's ability to work through the transformation and pay them more: the only sensible form of wealth redistribution that will be generated by the increased productivity due to artificial intelligence is through better jobs and better pay."
The scholars who spoke at the OECD showed that systemic thinking is needed in order to: improve the metrics by which artificial intelligence is evaluated, introduce ethics into the design, consider all stakeholders in the development of policies that affect its application.
In July 2020 at the International Conference on Machine Learning, the "participatory" approach was discussed: those who produce artificial intelligence must listen to the voice of those who will be affected by it.
Technology is a historical construct. And the quality that makes it enduring is its adaptability in changing contexts. The impact of artificial intelligence will be great. It will increase productivity and have social consequences: to think about. Because preventing suffering is possible, right and affordable.
OECD - Stefano Scarpetta
Luca De Biase - Intelligenza artificiale e lavoro. Conferenza all’OECD
Francesco Cicione, Luca De Biase, Innovazione armonica. Un senso di futuro, 2021 Rubettino Entopan
In Italian. Jessica Powell, La grande distruzione, 2020 Campanotto.
Naomi Oreskes, Why Trust Science?, 2019 Princeton University Press. In Italian: Perché fidarsi della scienza, 2021 Bollati Boringhieri.