Paper by Merve Hickok: “Public entities around the world are increasingly deploying artificial intelligence (AI) and algorithmic decision-making systems to provide public services or to use their enforcement powers. The rationale for the public sector to use these systems is similar to private sector: increase efficiency and speed of transactions and lower the costs. However, public entities are first and foremost established to meet the needs of the members of society and protect the safety, fundamental rights, and wellbeing of those they serve. Currently AI systems are deployed by the public sector at various administrative levels without robust due diligence, monitoring, or transparency. This paper critically maps out the challenges in procurement of AI systems by public entities and the long-term implications necessitating AI-specific procurement guidelines and processes. This dual-prong exploration includes the new complexities and risks introduced by AI systems, and the institutional capabilities impacting the decision-making process. AI-specific public procurement guidelines are urgently needed to protect fundamental rights and due process…(More)”.
Tales from a Robotic World: How Intelligent Machines Will Shape Our Future
Book by Dario Floreano and Nicola Nosengo: “Tech prognosticators promised us robots—autonomous humanoids that could carry out any number of tasks. Instead, we have robot vacuum cleaners. But, as Dario Floreano and Nicola Nosengo report, advances in robotics could bring those rosy predictions closer to reality. A new generation of robots, directly inspired by the intelligence and bodies of living organisms, will be able not only to process data but to interact physically with humans and the environment. In this book, Floreano, a roboticist, and Nosengo, a science writer, bring us tales from the future of intelligent machines—from rescue drones to robot spouses—along with accounts of the cutting-edge research that could make it all possible.
These stories from the not-so-distant future show us robots that can be used for mitigating effects of climate change, providing healthcare, working with humans on the factory floor, and more. Floreano and Nosengo tell us how an application of swarm robotics could protect Venice from flooding, how drones could reduce traffic on the congested streets of mega-cities like Hong Kong, and how a “long-term relationship model” robot could supply sex, love, and companionship. After each fictional scenario, they explain the technologies that underlie it, describing advances in such areas as soft robotics, swarm robotics, aerial and mobile robotics, humanoid robots, wearable robots, and even biohybrid robots based on living cells. Robotics technology is no silver bullet for all the world’s problems—but it can help us tackle some of the most pressing challenges we face…(More)”.
Google’s new AI can hear a snippet of song—and then keep on playing
Article by Tammy Xu: “The new AI system can generate natural sounds and voices after being prompted with a few seconds of audio.
AudioLM, developed by Google researchers, produces sounds that match the style of reminders, including complex sounds like piano music or human voices, in a way that is nearly indistinguishable from original record. The technique shows promise in terms of speeding up the training of AI to generate audio, and it could eventually be used to automatically generate music to accompany videos.
AI-generated audio has become ubiquitous: voices on home assistants like Alexa use natural language processing. AI music systems like OpenAI’s Jukebox have produced impressive results, but most current techniques require people to prepare transcriptions and label training data based on text, which does It takes a lot of time and human labor. For example, Jukebox uses text-based data to generate lyrics.
AudioLM, described in a non-peer-reviewed paper Last month was different: it didn’t require transcription or labeling. Instead, an audio database is fed into the program, and machine learning is used to compress the audio files into audio clips, called “tokens,” without losing too much information. This encrypted training data is then fed into a machine learning model that uses natural language processing to learn the audio samples.
To generate sound, a few seconds of audio is fed into AudioLM, then predict what happens next. This process is similar to how language models like GPT-3 predict sentences and words that often follow one another.
Sound clip released by the team sounds quite natural. In particular, piano music created with AudioLM sounded more fluid than piano music created with existing AI techniques, which tends to sound chaotic…(More)”.
The Equality Machine: Harnessing Digital Technology for a Brighter, More Inclusive Future
Book by Orly Lobel: “Much has been written about the challenges tech presents to equality and democracy. But we can either criticize big data and automation or steer it to do better. Lobel makes a compelling argument that while we cannot stop technological development, we can direct its course according to our most fundamental values.
With provocative insights in every chapter, Lobel masterfully shows that digital technology frequently has a comparative advantage over humans in detecting discrimination, correcting historical exclusions, subverting long-standing stereotypes, and addressing the world’s thorniest problems: climate, poverty, injustice, literacy, accessibility, speech, health, and safety.
Lobel’s vivid examples—from labor markets to dating markets—provide powerful evidence for how we can harness technology for good. The book’s incisive analysis and elegant storytelling will change the debate about technology and restore human agency over our values…(More)”.
The Transformations of Science
Essay by Geoff Anders: “In November of 1660, at Gresham College in London, an invisible college of learned men held their first meeting after 20 years of informal collaboration. They chose their coat of arms: the royal crown’s three lions of England set against a white backdrop. Their motto: “Nullius in verba,” or “take no one’s word for it.” Three years later, they received a charter from King Charles II and became what was and remains the world’s preeminent scientific institution: the Royal Society.
Three and a half centuries later, in July of 2021, even respected publications began to grow weary of a different, now constant refrain: “Trust the science.” It was a mantra everyone was supposed to accept, repeated again and again, ad nauseum.
This new motto was the latest culmination of a series of transformations science has undergone since the founding of the Royal Society, reflecting the changing nature of science on one hand, and its expanding social role on the other.
The present world’s preeminent system of thought now takes science as a central pillar and wields its authority to great consequence. But the story of how that came to be is, as one might expect, only barely understood…
There is no essential conflict between the state’s use of the authority of science and the health of the scientific enterprise itself. It is easy to imagine a well-funded and healthy scientific enterprise whose authority is deployed appropriately for state purposes without undermining the operation of science itself.
In practice, however, there can be a tension between state aims and scientific aims, where the state wants actionable knowledge and the imprimatur of science, often far in advance of the science getting settled. This is especially likely in response to a disruptive phenomenon that is too new for the science to have settled yet—for example, a novel pathogen with unknown transmission mechanisms and health effects.
Our recent experience of the pandemic put this tension on display, with state recommendations moving against masks, and then for masks, as the state had to make tactical decisions about a novel threat with limited information. In each case, politicians sought to adorn the recommendations with the authority of settled science; an unfortunate, if understandable, choice.
This joint partnership of science and the state is relatively new. One question worth asking is whether the development was inevitable. Science had an important flaw in its epistemic foundation, dating back to Boyle and the Royal Society—its failure to determine the proper conditions and use of scientific authority. “Nullius in verba” made some sense in 1660, before much science was settled and when the enterprise was small enough that most natural philosophers could personally observe or replicate the experiments of the others. It came to make less sense as science itself succeeded, scaled up, and acquired intellectual authority. Perhaps a better answer to the question of scientific authority would have led science to take a different course.
Turning from the past to the future, we now face the worrying prospect that the union of science and the state may have weakened science itself. Some time ago, commentators raised the specter of scientific slowdown, and more recent analysis has provided further justification for these fears. Why is science slowing? To put it simply, it may be difficult to have science be both authoritative and exploratory at the same time.
When scientists are meant to be authoritative, they’re supposed to know the answer. When they’re exploring, it’s okay if they don’t. Hence, encouraging scientists to reach authoritative conclusions prematurely may undermine their ability to explore—thereby yielding scientific slowdown. Such a dynamic may be difficult to detect, since the people who are supposed to detect it might themselves be wrapped up in a premature authoritative consensus…(More)”.
Governing the Environment-Related Data Space
Stefaan G. Verhulst, Anthony Zacharzewski and Christian Hudson at Data & Policy: “Today, The GovLab and The Democratic Society published their report, “Governing the Environment-Related Data Space”, written by Jörn Fritzenkötter, Laura Hohoff, Paola Pierri, Stefaan G. Verhulst, Andrew Young, and Anthony Zacharzewski . The report captures the findings of their joint research centered on the responsible and effective reuse of environment-related data to achieve greater social and environmental impact.
Environment-related data (ERD) encompasses numerous kinds of data across a wide range of sectors. It can best be defined as data related to any element of the Driver-Pressure-State-Impact-Response (DPSIR) Framework. If leveraged effectively, this wealth of data could help society establish a sustainable economy, take action against climate change, and support environmental justice — as recognized recently by French President Emmanuel Macron and UN Secretary General’s Special Envoy for Climate Ambition and Solutions Michael R. Bloomberg when establishing the Climate Data Steering Committee.
While several actors are working to improve access to, as well as promote the (re)use of, ERD data, two key challenges that hamper progress on this front are data asymmetries and data enclosures. Data asymmetries occur due to the ever-increasing amounts of ERD scattered across diverse actors, with larger and more powerful stakeholders often maintaining unequal access. Asymmetries lead to problems with accessibility and findability (data enclosures), leading to limited sharing and collaboration, and stunting the ability to use data and maximize its potential to address public ills.
The risks and costs of data enclosure and data asymmetries are high. Information bottlenecks cause resources to be misallocated, slow scientific progress, and limit our understanding of the environment.
A fit-for-purpose governance framework could offer a solution to these barriers by creating space for more systematic, sustainable, and responsible data sharing and collaboration. Better data sharing can in turn ease information flows, mitigate asymmetries, and minimize data enclosures.
And there are some clear criteria for an effective governance framework…(More)”
AI & Cities: Risks, Applications and Governance
Report by UN Habitat: “Artificial intelligence is manifesting at an unprecedented rate in urban centers, often with significant risks and little oversight. Using AI technologies without the appropriate governance mechanisms and without adequate consideration of how they affect people’s human rights can have negative, even catastrophic, effects.
This report is part of UN-Habitat’s strategy for guiding local authorities in realizing a people-centered digital transformation process in their cities and settlements…(More)”.
Realistic Reasons to be Bullish on Nudging
Essay by Ed Bradon: “Nudges are a valuable, modestly resourced and, as we shall see, dramatically underused way of improving people’s lives. Abandoning them now would be like discovering aspirin then immediately shutting down production because it doesn’t cure cancer.
Nudging’s value stems from its modest but unusual success in solving two hard problems. One is changing people’s behavior, in a sustainable way, in challenging contexts such as health, crime, and education, in the messiness of the real world. The second is getting stuff done in large organizations, particularly government. Most attempts at either one of these fail: over 80 percent of social projects and programs don’t work; big reform efforts are generally stymied, or backfire.
By contrast, nudges do get implemented—albeit with a lot of hard work behind the scenes—and when they are they tend to do some good. Looking at trials from two nudge units, Stefano DellaVigna and Elizabeth Linos find that a sample of low-cost, light-touch nudges do better than their control groups by 8 percent on average. In a landscape littered with failures and overclaiming, small robust improvements that affect thousands of people are worth having…
But might we still be overinvesting in nudges? Perhaps they have proven so popular that the best opportunities have been exhausted, making it time to redeploy resources elsewhere?
Unfortunately, the opposite is true: we haven’t picked even the lowest hanging fruit. A back-of-the-envelope calculation for central governments can illustrate this opportunity. A typical government might have 10 large departments of state (a department for education, for example), each with 10 directorates (such as the organization in charge of apprenticeships and technical education). And each of these could easily have 20 nudge-able systems (a system through which young people can sign up for apprenticeships, say). Each system can accommodate multiple nudges: you could try boosting sign-ups by pre-filling parts of the form, for example, while also reminding students at a timely moment. One government × ten departments × ten directorates × twenty systems × three nudges each gets us a total of 6,000 possible nudges….(More)”.
Existing and Potential Use Cases for Blockchain in Public Procurement
Paper by Pedro Telles: “The purpose of this paper is to assess the possibility of using blockchain technology in the realm of public procurement within the EU, particularly in connection with the award of public contracts. In this context, blockchain is used as an umbrella term covering IT technologies and cryptographic solutions used to generate consensus on a distributed ledger.
The paper starts by elaborating how blockchains and distributed ledgers work in general, includ-ing the drawbacks of different blockchain models and implementations, before looking into recent developments for distributed consensus that may herald some potential.
As for public procurement, blockchain has been used in three real use cases in Aragon (Spain), Colombia and Peru, with the first two not passing from the pilot stage and the latter being deployed in production. These use cases are analysed with an emphasis in what can be learned from the difficulties faced by each project.
Finally, this paper will posit two specific areas of EU public procurement practice that might benefit from the use of blockchain technology. The first is on data management and accessibility where current solutions have been unsuccessful, such as cross-border certification data as required by the European Single Procurement Document (ESPD) and e-Certis or the difficulties with contract data collection and publication. The second, on situations of clear lack of confidence on public powers, where the downsides of blockchain technologies and the costs they entail are an advantage. Even considering these potential scenarios, the overall perspective is that the benefits of blockchain solutions do not really provide much value in the context of public procurement for now…(More)”.
How to stop our cities from being turned into AI jungles
Stefaan G. Verhulst at The Conversation: “As artificial intelligence grows more ubiquitous, its potential and the challenges it presents are coming increasingly into focus. How we balance the risks and opportunities is shaping up as one of the defining questions of our era. In much the same way that cities have emerged as hubs of innovation in culture, politics, and commerce, so they are defining the frontiers of AI governance.
Some examples of how cities have been taking the lead include the Cities Coalition for Digital Rights, the Montreal Declaration for Responsible AI, and the Open Dialogue on AI Ethics. Others can be found in San Francisco’s ban of facial-recognition technology, and New York City’s push for regulating the sale of automated hiring systems and creation of an algorithms management and policy officer. Urban institutes, universities and other educational centres have also been forging ahead with a range of AI ethics initiatives.
These efforts point to an emerging paradigm that has been referred to as AI Localism. It’s a part of a larger phenomenon often called New Localism, which involves cities taking the lead in regulation and policymaking to develop context-specific approaches to a variety of problems and challenges. We have also seen an increased uptake of city-centric approaches within international law frameworks…
Below are ten principles to help systematise our approach to AI Localism. Considered together, they add up to an incipient framework for implementing and assessing initiatives around the world:…(More)”.