Every “intelli-agent” human will soon be in part a machine. And viceversa.
To make sense of the enormous amount of data around us we need to co-operate with machines. And it will be a challenge for both.
Key takeaways:
- To unlock the power of data at scale we need machines;
- Machines can empower and complement humans, but also viceversa;
- Driving the evolution of society through human-machine interfaces is a priority and a design challenge (not technological);
- Blade Runner might be now in the past, but still we have a long way to run before developing a true understanding of how humans and machines can co-operate and be intelli-agents, together.
While we were busy doing something else, we went through the age of the database, in which a few data describe the “who” of things, and then through the age of profile, where the “who” is enriched by fragments of “where, how, when and why”.
Two ages still relatively easy to understand by humans, but maybe the future has some new post in the feed for us: the amount of data about who, what, why, how, when and where of things could soon be so big as to become inhuman.
Inhuman, dis-human, dysfunctional to the human, perhaps almost perfect on a syntactic level, but progressively encrypted to human sensors.
Is our digital twin learning a language that is simply too complex for us? Maybe. And this is happening in background.
What a tragic destiny then the human one: installing sensors and intelligence in machines with the aim of knowing everything and then being pulled down to knowing nothing! But, aware or not, we already have the solution to this problem. From if-then-else to machine learning, artificial agents are made to deal with data at scale and extract relationships, patterns and graphs.
Yes, algorithms can outperform us in making sense of this complexity… but this alliance has a deeper reason to exist than a “scale/skill” gap. It is a necessary alliance, because we are designed for different roles and we are not interchangeable.
The difference between us and artificial agents is about a 100% human prerogative, the unattainable operational extreme for a machine: I’m talking about free will.
The descriptive and predictive determinism of data, what Cosimo Accoto defines “archive and oracle”, is not really of men and women. Human beings exercise their agency through little information, often incomplete, and use instinct and experience to move forward. We have not been made to optimise an analytical function while we are short for our morning train. It’s no thing we can emotionally handle.
The human runtime knows only the «best-effort mode».
Human beings need to simplify before making decisions while still operating like a black box. Machines and algorithms, on the other hand, are voracious up to the limit of processing and storage, they can expand millions of scenarios and deepen them at great speed. Artificial choices don’t have emotions, at the moment at least. The risk is calculated, while for the human being the risk is undefined and incalculable, yet tolerated.
An intelligent agent operating for 200 years could achieve astonishing performance while a human condemned to eternal youth would probably end up being depressed, surrounded by either “happy and gone” and “sad and everlasting” memories, by pains with a precise place and time, which are there to remember the past instead of the future. An inhuman life, a life blocked by a mass of information that cannot be emotionally managed.
It is at this level, the level of limits, that human and artificial meet and take their hands. Our destiny is to be different for a long time, but we both have limitations which represent the most unattainable aspiration for the other. And the complement to one.
And, as always, we come back to Blade Runner. And to Kubrick. The eternal chase between man and machine is perhaps the most beautiful thing we have in common.
Riccardo is Beretta’s Digital Business Development Manager. Graduated in Engineering, he has served in various marketing roles before focusing on business transformation and digital platforms since 2016. In the last decade, he has developed a personal interest in exploring the potential of computational privacy/trust towards a more effective and sustainable data driven society. With the aim of contributing to a wide and open conversation about MIT’s OPAL project, he published “The end of Personalinvasion” (2019) and “OPAL and Code-Contract: a model of responsible and efficient data ownership for citizens and business” (2018). He is a member of the advisory board of “Quota 8000 — Service Innovation Hub” at TEH Ambrosetti. Since 2000 he experiments with digital art as an independent researcher. Some of his projects have been acquired from the permanent ArtBase collection of Rhizome.org — NY (2002) and exhibited at the Montreal Biennial of Contemporary Art (2004), as well as at Interface Monthly (London, 2016, by The Trampery and Barbican). In 2015, he released FAC3, one of the first artworks in the world to use artificial intelligence. He is married and father of two. Want to drop a line? → riccardo [d ot) zanardelli {at} gmail [ do t} com
