Surveillance, Companionship, and Entertainment: The Ancient History of Intelligent Machines

Curated on Posted on by Stefaan Verhulst

Essay by E.R. Truitt: “Robots have histories that extend far back into the past. Artificial servants, autonomous killing machines, surveillance systems, and sex robots all find expression from the human imagination in works and contexts beyond Ovid (43 BCE to 17 CE) and the story of Pygmalion in cultures across Eurasia and North Africa. This long history of our human-machine relationships also reminds us that our aspirations, fears, and fantasies about emergent technologies are not new, even as the circumstances in which they appear differ widely. Situating these objects, and the desires that create them, within deeper and broader contexts of time and space reveals continuities and divergences that, in turn, provide opportunities to critique and question contemporary ideas and desires about robots and artificial intelligence (AI).

As early as 3,000 years ago we encounter interest in intelligent machines and AI that perform different servile functions. In the works of Homer (c. eighth century BCE) we find Hephaestus, the Greek god of smithing and craft, using automatic bellows to execute simple, repetitive labor. Golden handmaidens, endowed with characteristics of movement, perception, judgment, and speech, assist him in his work. In his “Odyssey,” Homer recounts how the ships of the Phaeacians perfectly obey their human captains, detecting and avoiding obstacles or threats, and moving “at the speed of thought.” Several centuries later, around 400 BCE, we meet Talos, the giant bronze sentry, created by Hephaestus, that patrolled the shores of Crete. These examples from the ancient world all have in common their subservient role; they exist to serve the desires of other, more powerful beings — either gods or humans — and even if they have sentience, they lack autonomy. Thousands of years before Karel Čapek introduced the term “robot” to refer to artificial slaves, we find them in Homer….(More)”.

Conceptualizing AI literacy: An exploratory review

Curated on Posted on by Stefaan Verhulst

Paper by Davy Tsz KitNg, Jac Ka LokLeung, Samuel K.W.Chu, and Maggie QiaoShen: “Artificial Intelligence (AI) has spread across industries (e.g., business, science, art, education) to enhance user experience, improve work efficiency, and create many future job opportunities. However, public understanding of AI technologies and how to define AI literacy is under-explored. This vision poses upcoming challenges for our next generation to learn about AI. On this note, an exploratory review was conducted to conceptualize the newly emerging concept “AI literacy”, in search for a sound theoretical foundation to define, teach and evaluate AI literacy. Grounded in literature on 30 existing peer-reviewed articles, this review proposed four aspects (i.e., know and understand, use, evaluate, and ethical issues) for fostering AI literacy based on the adaptation of classic literacies. This study sheds light on the consolidated definition, teaching, and ethical concerns on AI literacy, establishing the groundwork for future research such as competency development and assessment criteria on AI literacy….(More)”.

Perspectives on Platform Regulation

Curated on Posted on by Stefaan Verhulst

Open Access Book edited by Judit Bayer, Bernd Holznage, Päivi Korpisaari and Lorna Woods: “Concepts and Models of Social Media GovernanceOnline social media platforms set the agenda and structure for public and private communication in our age. Their influence and power is beyond any traditional media empire. Their legal regulation is a pressing challenge, but currently, they are mainly governed by economic pressures. There are now diverse legislative attempts to regulate platforms in various parts of the world. The European Union and most of its Member States have historically relied on soft law, but are now looking to introduce regulation.

Leading researchers of the field analyse the hard questions and the responses given by various states. The book offers legislative solutions from various parts of the world, compares regulatory concepts and assesses the use of algorithms….(More)”.

Decolonizing Innovation

Curated on Posted on by Stefaan Verhulst

Essay by Tony Roberts and Andrea Jimenez Cisneros: “In order to decolonize global innovation thinking and practice, we look instead to indigenous worldviews such as Ubuntu in Southern Africa, Swaraj in South Asia, and Buen Vivir in South America. Together they demonstrate that a radically different kind of innovation is possible.

The fate of Kenya’s Silicon Savannah should serve as a cautionary tale about exporting Western models to the Global South.

The fate of Kenya’s Silicon Savannah should serve as a cautionary tale about exporting Western models to the Global South. The idea of an African Silicon Valley emerged around 2011 amidst the digital technology ecosystem developing in Nairobi. The success of Nairobi’s first innovation hub inspired many imitators and drove ambitious plans by the government to build a new innovation district in the city. The term “Silicon Savannah” captured these aspirations and featured in a series of blog posts, white papers, and consultancy reports. Advocates argued that Nairobi could leapfrog other innovation centers due to lower entry barriers and cost advantages.

These promises caught the attention of many tech entrepreneurs and policymakers—including President Barack Obama, who cohosted the 2015 Global Entrepreneurship Summit in Kenya. As part of its Silicon Savannah vision, the Kenyan government proposed to build a “smart city” called Konza Technopolis in the south of Nairobi. This government-led initiative—designed with McKinsey consultants—was supposed to help turn Kenya into a “middle-income country providing a high quality life to all its citizens by the year 2030.” The city was proposed to attract investors, create jobs at a mass scale, and use technology to manage the city effectively and efficiently. Its website identified Konza as the place where “Africa’s silicon savannah begins.” Years later, the dream remains unfulfilled. As Kenyan writer Carey Baraka’s has recently detailed, the plan has only reinforced existing inequalities as it caters mainly to international multinationals and the country’s wealthy elite.

One of the most important lessons to be derived from studying such efforts to import foreign technologies and innovation models is that they inevitably come with ideological baggage. Silicon Valley is not just a theoretical model for economic growth: it represents a whole way of life, carrying with it all kinds of implications for how people think about themselves, each other, and their place in the world. Venture capital pitching sessions prize what is most monetizable, what stands to deliver the greatest return on investment, and what offers the earliest exit opportunities. Breznitz is right to criticize this way of thinking, but similar worries arise about his own examples, which say little about environmental sustainability or maintaining the integrity of local communities. Neoliberal modes of private capital accumulation are not value neutral, and we must be sensitive to the way innovation models are situated in uneven structures of power, discourse, and resource distribution…(More)”.

Randomistas vs. Contestistas

Curated on Posted on by Stefaan Verhulst

Excerpt by By Beth Simone Noveck: “Social scientists who either run experiments or conduct systematic reviews tend to be fervent proponents of the value of RCTs. But that evidentiary hierarchy—what some people call the “RCT industrial complex”—may actually lead us to discount workable solutions just because there is no accompanying RCT.

A trawl of the solution space shows that successful interventions developed by entrepreneurs in business, philanthropy, civil society, social enterprise, or business schools who promote and study open innovation, often by developing and designing competitions to source ideas, often come from more varied places. Uncovering these exciting social innovations lays bare the limitations of confining a definition of what works only to RCTs.

Many more entrepreneurial and innovative solutions are simply not tested with an RCT and are not the subject of academic study. As one public official said to me, you cannot saddle an entrepreneur with having to do a randomized controlled trial (RCT), which they do not have the time or know-how to do. They are busy helping real people, and we have to allow them “to get on with it.”

For example, MIT Solve, which describes itself as a marketplace for socially impactful innovation designed to identify lasting solutions to the world’s most pressing problems. It catalogs hundreds of innovations in use around the world, like Faircap, a chemical-free water filter used in Mozambique, or WheeLog!, an application that enables individuals and local governments to share accessibility information in Tokyo.

Research funding is also too limited (and too slow) for RCTs to assess every innovation in every domain. Many effective innovators do not have the time, resources, or know-how to partner with academic researchers to conduct a study, or they evaluate projects by some other means.

There are also significant limitations to RCTs. For a start, systematic evidence reviews are quite slow, frequently taking upward of two years, and despite published standards for review, there is a lack of transparency. Faster approaches are important. In addition, many solutions that have been tested with an RCT clearly do not work. Interestingly, the first RCT in an area tends to produce an inflated effect size….(More)”.

Data and Society: A Critical Introduction

Curated on Posted on by Stefaan Verhulst

Book by Anne Beaulieu and Sabina Leonelli: “Data and Society: A Critical Introduction investigates the growing importance of data as a technological, social, economic and scientific resource. It explains how data practices have come to underpin all aspects of human life and explores what this means for those directly involved in handling data. The book

  • fosters informed debate over the role of data in contemporary society
  • explains the significance of data as evidence beyond the “Big Data” hype
  • spans the technical, sociological, philosophical and ethical dimensions of data
  • provides guidance on how to use data responsibly
  • includes data stories that provide concrete cases and discussion questions.

Grounded in examples spanning genetics, sport and digital innovation, this book fosters insight into the deep interrelations between technical, social and ethical aspects of data work…(More)”.

Collective innovation is key to the lasting successes of democracies

Curated on Posted on by Stefaan Verhulst

Article by Kent Walker and Jared Cohen: “Democracies across the world have been through turbulent times in recent years, as polarization and gridlock have posed significant challenges to progress. The initial spread of COVID-19 spurred chaos at the global level, and governments scrambled to respond. With uncertainty and skepticism at an all-time high, few of us would have guessed a year ago that 66 percent of Americans would have received at least one vaccine dose by now. So what made that possible?

It turns out democracies, unlike their geopolitical competitors, have a secret weapon: collective innovation. The concept of collective innovation draws on democratic values of openness and pluralism. Free expression and free association allow for cooperation and scientific inquiry. Freedom to fail leaves room for risk-taking, while institutional checks and balances protect from state overreach.

Vaccine development and distribution offers a powerful case study. Within days of the coronavirus being first sequenced by Chinese researchers, research centers across the world had exchanged viral genome data through international data-sharing initiatives. The Organization for Economic Cooperation and Development found that 75 percent of COVID-19 research published after the outbreak relied on open data. In the United States and Europe, in universities and companies, scientists drew on open information, shared research, and debated alternative approaches to develop powerful vaccines in record-setting time.

Democracies’ self- and co-regulatory frameworks have played a critical role in advancing scientific and technological progress, leading to robust capital markets, talent-attracting immigration policies, world-class research institutions, and dynamic manufacturing sectors. The resulting world-leading productivity underpins democracies’ geopolitical influence….(More)”.

If We Can Report on the Problem, We Can Report on the Solution

Curated on Posted on by Stefaan Verhulst

David Bornstein and Tina Rosenberg in the New York Times: “After 11 years and roughly 600 columns, this is our last….

David Bornstein: Tina, in a decade reporting on solutions, what’s the most important thing you learned?

Tina Rosenberg: This is a strange lesson for a column about new ideas and innovation, but I learned that they’re overrated. The world (mostly) doesn’t need new inventions. It needs better distribution of what’s already out there.

Some of my favorite columns were about how to take old ideas or existing products and get them to new people. As one of our columns put it, “Ideas Help No One on a Shelf. Take Them to the World.” There are proven health strategies, for example, that never went anywhere until some folks dusted them off and decided to spread them. It’s not glamorous to copy another idea. But those copycats are making a big difference.

David: I totally agree. The opportunity to learn from other places is hugely undertapped.

I mean, in the United States alone, there are over 3,000 counties. The chance that any one of them is struggling with big problems — mental health, addiction, climate change, diabetes, Covid-19, you name it — is pretty much 100 percent. But the odds that any place is actually using one of the most effective approaches to deal with its problems is quite low.

As you know, I used to be a computer programmer, and I’m still a stats nerd. With so many issues, there are “positive deviants” — say, 2 percent or 3 percent of actors who are getting significantly better results than the norm. Finding those outliers, figuring out what they’re doing that’s different, and sharing the knowledge can really help. I saw this in my reporting on childhood trauma, chronic homelessness and hospital safety, to name a few areas….(More)”

Open science, data sharing and solidarity: who benefits?

Curated on Posted on by Stefaan Verhulst

Report by Ciara Staunton et al: “Research, innovation, and progress in the life sciences are increasingly contingent on access to large quantities of data. This is one of the key premises behind the “open science” movement and the global calls for fostering the sharing of personal data, datasets, and research results. This paper reports on the outcomes of discussions by the panel “Open science, data sharing and solidarity: who benefits?” held at the 2021 Biennial conference of the International Society for the History, Philosophy, and Social Studies of Biology (ISHPSSB), and hosted by Cold Spring Harbor Laboratory (CSHL)….(More)”.

Articulating the Role of Artificial Intelligence in Collective Intelligence: A Transactive Systems Framework

Curated on Posted on by Stefaan Verhulst

Paper by Pranav Gupta and Anita Williams Woolley: “Human society faces increasingly complex problems that require coordinated collective action. Artificial intelligence (AI) holds the potential to bring together the knowledge and associated action needed to find solutions at scale. In order to unleash the potential of human and AI systems, we need to understand the core functions of collective intelligence. To this end, we describe a socio-cognitive architecture that conceptualizes how boundedly rational individuals coordinate their cognitive resources and diverse goals to accomplish joint action. Our transactive systems framework articulates the inter-member processes underlying the emergence of collective memory, attention, and reasoning, which are fundamental to intelligence in any system. Much like the cognitive architectures that have guided the development of artificial intelligence, our transactive systems framework holds the potential to be formalized in computational terms to deepen our understanding of collective intelligence and pinpoint roles that AI can play in enhancing it….(More)”