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- Convenor:
-
Agata Bisping
(AGH University of Krakow)
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- Format:
- Workshop
- Location:
- Hevre
Short Abstract
In the week that science and technology researchers from around the world arrive in Kraków for EASST2026, we're opening that conversation up to the city. One evening, four talks, one bar.
Description
AI writes job applications. An algorithm decides where the ambulance goes. The city installs sensors nobody can see, which see everything. Technological change doesn't only happen in a lab, it happens in Wesoła, in Kazimierz, on the number 502 bus, and in the queue at the clinic.
SCI BARS borrows from the British science in a bar tradition and from French cafés scientifiques: research leaves the lecture hall and pulls up a stool. No lectern, no slides crowded with graphs, no sentence beginning "as the meta-analysis demonstrated." Someone talks about their work the way they'd tell a friend about it. Then the audience asks questions, and the questions run the evening, not the schedule.
There's one rule: if someone didn't follow, that's not their fault.
Four speakers (from any career stage or outside academia) will lead a talk about where science, technology and the future meet society. We're interested in, among others:
• algorithms and automation in everyday life - work, care, housing, transport
• who imagines the future and how: forecasts, scenarios, promises, disappointments
• bodies, health and data - from health apps to AI - assisted diagnosis
• climate, energy, infrastructure: the technologies meant to save us (or not)
• the city as a laboratory - sensors, platforms, "smart" solutions and what they cost
• technological promises from the past that never arrived, and what they teach us
As long as there's real research or hands-on experience behind the talk, you don't need to be attending EASST2026. You don't need to live in Kraków. [Apply via link below]
Four 15-minute talks, a short round of questions after each, then an open conversation at the bar with nobody moderating too hard. Talks are in Polish or English, depending on the speaker; the audience will be mixed, local and international. Slides aren't needed; if you really want them, three maximum.
| Workshop Sign Up Link | https://nomadit.co.uk/conference/easst2026/paper-form/20473/late |
| Second Workshop Sign Up Link | |
| Third Workshop Sign Up Link |
Accepted contributions
Short abstract
The first 21 cards of the tarot deck can give us material to interrogate the terrible, boring stories being told about the future by authoritarians and the tech industry. This talk outlines what these terrible and boring stories are and experiments with telling other ones.
Long abstract
The systems are broken, we hear. Work is precarious, politics polarised, and even the weather feels like a threat. Uncertainty reigns, and to resolve it, we turn to reassuring stories about futures where ‘numbers go up’ and everything is as it was before, only faster, and maybe with more AI. Creating this faster, more productive, machine-enabled future involves a series of bargains: giving away attention and intimate information to apps, sacrificing water and energy for the data centres that power them. An even bigger bargain comes in losing the ability to imagine different futures. This intervention describes the current narrative modes employed by the tech industry to address cultural experiences of uncertainty. These include linear narrative forms, putting 'technology' as a main character, and recourse to a mythic pattern of a 'hero's journey' that allows authoritarian strongmen to advance their own interests. Using the first 21 cards of the tarot deck, this talk investigates how we could tell other stories about the future, and how these stories might spark different action towards social, ecological or technological change.
Short abstract
As a child, I bought into grand technoscientific visions from Dolly the Sheep to Jurassic dreams. But as hype shaped my career, reality fell short. This is my story of navigating bio-hype, demanding accountability, and trying to take my career back from science.
Long abstract
I built my academic aspirations on grand technoscientific promises. Raised during the hype of Dolly the sheep, I was sold a future where gene editing, synthetic biology, and endless technological solutions would effortlessly fix complex societal and biological crises.
Driven by this optimism, I pursued research expecting groundbreaking progress. Instead, I found an academic ecosystem trapped in a cycle of speculative bio-hype where complex ethical and systemic issues are routinely flattened into market-ready, quick-fix technologies, and the technological solutions that were promised are hardly delivered. Over time, I realized how deeply these inflated promises dictate career paths, funding allocations, and public expectations. We are constantly promised revolutionary solutions to human vulnerability, yet handed incremental technological patches disguised as monumental breakthroughs. As someone whose career trajectory was actively shaped by these seductive visions, I began to ask a fundamental question: Where is the real return on our investment? This talk is a critical personal reflection on navigating the illusion of technological solutions, particularly on working class people being raised in the periphery of global capitalism. Tracing my journey through evolutionary biology and bioethics, I confront the gap between genuine scientific progress and speculative imaginations. Ultimately, it is a story of reclaiming agency, demanding conceptual clarity, exposing technocratic shortcuts, and figuring out how to take our careers and public trust back from science.
Short abstract
We expect AI to solve our problems. More often, it makes existing ones visible faster. Drawing on twenty years inside technology organizations I will show why automation does not remove coordination problems but scales them. If we save time thanks to AI, what happens to that time?
Long abstract
For twenty years I have worked inside technology organizations: an award-winning agency, live gaming entering four regulated markets, a scaling SaaS startup, and 5G/6G R&D at Ericsson. I map where delivery breaks down and why.
Across all of them I saw the same pattern. Organizations adopt technology expecting it to solve a problem. What it usually does is make an existing problem visible faster.
One example. A product supported in 27 languages. Design defines how many characters the interface can hold. Translators fit within that limit or flag an exception. Frontend handles both extremes. Testers try to break it. If one of these four roles does not know about the other three, the interface falls apart. No one is at fault: everyone did their part correctly. Automation does not remove this coordination problem. It scales it.
I want to talk about what happens when AI enters organizations that never made their own decision-making visible. Who owns a decision when an algorithm proposes it? What happens to people whose competence quietly compensated for structural weakness?
Recent research found that students who outsourced homework to AI scored 18 to 24 percent worse on exams. Not because the tool was bad, but because the time saved was removed from learning instead of reinvested.
Every organization automating work faces the same question: what happens to the time we save?
Short abstract
A tidal surge floods the city of Hull, knocking out terrestrial phones. Emergency services rely on their contracted backup, Elon Musk’s Starlink, only to find the service has been restricted by the US government due to a geopolitical spat. Hear what we learnt from playing out this scenario.
Long abstract
Satellite technology has quietly become an invisible international infrastructure. It is often governed by a kind of technology feudalism: complex combinations of private and national interests. This talk recounts a 2025 simulation of a fictional crisis where these hidden systems of power became visible.
A massive tidal surge floods the city of Hull, knocking out terrestrial phones. The emergency services rely on their contracted backup, Elon Musk’s Starlink, only to find the service has been restricted by the US government due to a geopolitical spat over Greenland.
I will describe how the events played out in this exercise run with experts and in collaboration with colleagues at the UK Space Agency.
The outputs are valuable for bringing public attention to these technology risks (and also fairly entertaining). But what could have been achieved if we had involved the public from the start? I want to hear from the Sci Bar audience: what would you have done in the simulation and, more generally, what should we be doing to respond to the failed promise of a technological commons in Low Earth Orbit?
Short abstract
Children seem to grow up earlier, while teenagers enter adulthood later. Are algorithms, changing media and consumer culture pulling our ideas of age apart? A look at the growing gap between cultural and social age - and what might come after the teenager.
Long abstract
Something strange seems to be happening to age.
Ten-year-olds follow skincare routines, fashion aesthetics and influencers that not long ago would have been associated with teenagers. At the same time, a twelve-year-old, a sixteen-year-old and a twenty-two-year-old may now encounter many of the same cultural references through their social media feeds.
It would be easy to say that young people are simply growing up faster. Research suggests a more complicated picture. Large longitudinal studies show that teenagers are actually delaying many behaviours traditionally associated with growing up, including dating, paid work, driving and spending time outside the home without their parents.
This contradiction is where my talk begins. I want to bring research on adolescent behaviour, age compression, tween culture and social media together with what I see in my own work in fashion design and trend research for young consumers.
Categories such as “tween” and “teenager” have never been only about biology. Media, fashion and consumer culture have played a role in defining what different ages look like and how they behave. I am interested in what happens to these categories when personalised feeds increasingly cut across traditional age segmentation.
Could cultural age and social age be moving apart? And could technology be contributing to that shift?
If what young people watch, wear and want tells us less about their age, while the traditional markers of adulthood arrive later, what does being a teenager mean now? And what might it mean in the future
Short abstract
AI does not have to take our jobs to transform them. It can reduce human control while leaving responsibility intact. Using PPC specialists as a case, I show how, when everyone uses the same algorithms, advantage may come from who can interpret them better.
Long abstract
When we talk about AI, we usually ask whether machines will take our jobs. My research starts from a different possibility: what if AI does not remove humans from work, but removes their control while leaving them responsible for the outcome?
I study PPC specialists working with Google and Meta algorithms, drawing on 27 in-depth interviews, professional observation, and more than 1,000 online discussions. They already work in a world many other professions are only beginning to enter: algorithms make key decisions, while humans increasingly see the outcome but not the reasoning behind it.
Their work has not disappeared. It has changed. Specialists watch for anomalies, test hypotheses, compare experiences, and ask one another: “Is the algorithm doing this for you too?”
This creates two paradoxes. The less visible the system becomes, the more valuable human interpretation can become. And although thousands of organizations use the same algorithms, they do not achieve the same results. If everyone has access to the same technology, competitive advantage may come from who can read the system better: who notices the right signals, builds better explanations, and learns faster.
PPC specialists may therefore be a prototype of the future of work with AI: less human control, more machine-made decisions, and a growing value of interpretation, judgement, and responsibility.