Blog by Paul Cairney: “Wouldn’t it be nice if policy scholars and professionals could have frequent and fruitful discussions about policy and policymaking? Both professions could make valuable contributions to our understanding of policy design in a wider political context.
However, it is notoriously difficult to explain what policy is and how it is made, and academics and practitioners may present very different perspectives on what policymakers or governments do. Without a common reference point, how can they cooperate to discuss how to (say) improve policy or policymaking?
One starting point is to visualize policymaking to identify overlaps in perspectives. To that end, if academics and policymakers were to describe ‘the policy process’, could they agree on what it looks like? To help answer this question, in this post I’m presenting some commonly-used images in policy research, then inviting you to share images that you would use to sum up policy work…
One obstacle to a shared description is that we need different images for different aims, including:
To describe and explain what policymakers do. Academics describe one part of a complex policy process, accompanied by a technical language to understand each image.
To describe what policymakers need to do. Practitioners visualise a manageable number of aims or requirements (essential steps, stages, or functions), accompanied by a professional in-house language (such as in the Green Book).
To describe what they would like to do. Governments produce images of policymaking to tell stakeholders or citizens what they do, accompanied by an aspirational language related to what is expected of elected governments…(More)”.
Editorial by Suzanne Bakken: “In this editorial, I highlight 5 papers that address innovative informatics interventions—3 research studies and 2 reviews. The papers reflect a variety of information technologies and processes including mobile health (mHealth), behavioral nudges in the electronic health record (EHR), adaptive intervention framework, predictive models, and artificial intelligence (eg, machine learning, data mining, natural language processing). The interventions were designed to address important clinical and public health problems such as adherence to antiretroviral therapy for persons living with HIV (PLWH), opioid use disorder, and pain assessment and management, as well as aspects of healthcare quality including no-show rates for appointments and erroneous decisions, waste, and misuse of resources due to EHR choice architecture for clinician orders…(More)”.
Paper by Maèva Flayelle et al: “Gaming disorder was officially recognized as a disorder of addictive behaviour in the International Classification of Diseases 11th revision in 2019. Since then, other types of potentially problematic online behaviour have been discussed as possible candidates for inclusion in the psychiatric nosography of addictive disorders. Understanding these problematic online behaviours requires further study of the specific psychological mechanisms involved in their formation and maintenance. An important but underdeveloped line of research has examined the ways in which technology design features might influence users’ capacity to exert control over how they engage with and use websites and applications, thereby amplifying uncontrolled, and perhaps addictive, use. In this Review, we critically examine the available research on the relationships between technology design features and the loss of control and harms experienced by those who engage in online video gaming, online gambling, cybersexual activities, online shopping, social networking and on-demand TV streaming. We then propose a theory-driven general taxonomy of the design features of online applications that might promote uncontrolled and problematic online behaviours…(More)”.
Paper by Susan Ariel Aaronson: “In 2019, Shinzo Abe, then Prime Minister of Japan, stated that if the world wanted to achieve the benefits of the data-driven economy, members of the World Trade Organization should find a common approach to combining ‘data free flow with trust’. However, he never explained what these rules should look like and how nations might find an internationally accepted approach to such rules. In this paper, I argue that trade policy-makers must pay closer attention to users’ concerns if they truly want to achieve ‘data free flow with trust’. I begin with an examination of what the most recent digital trade/ecommerce agreements say about trust and discuss whether they actually meet user concerns. Next, I turn to three different examples of online problems that users have expressed concerns about, namely internet shutdowns/censorship, disinformation, and ransomware, describing how these may yield both trade distortions and less trust online. I argue that policy-makers should address these issues if they believe trade agreements should build trust in cross-border data flows. Moreover, I argue how policy-makers respond to user concerns is as important as what they include in trade agreements. Finally, I note that trade negotiators will need to rethink how they involve the broad public in digital trade policy-making, while recognizing that trade policy agreements may not be the best place to address these problems…(More)”.
Press Release: “Today, the signatories of the 2022 Code of Practice on Disinformation, including all major online platforms (Google, Meta, Microsoft, TikTok, Twitter), launched the novel Transparency Centre and published for the first time the baseline reports on how they turn the commitments from the Code into practice.
The new TransparencyCentre will ensure visibility and accountability of signatories’ efforts to fight disinformation and the implementation of commitments taken under the Code by having a single repository where EU citizens, researchers and NGOs can access and download online information.
For the first time with these baseline reports, platforms are providing insight and extensive initial data such as: how much advertising revenue flowing to disinformation actors was prevented; number or value of political ads accepted and labelled or rejected; instances of manipulative behaviours detected (i.e. creation and use of fake accounts); and information about the impact of fact-checking; and on Member States level…
All signatories have submitted their reports on time, using an agreed harmonised reporting template aiming to address all commitments and measures they signed onto. This is however not fully the case for Twitter, whose report is short of data, with no information on commitments to empower the fact-checking community. The next set of reports from major online platform signatories is due in July, providing further insight on the Code’s implementation and more stable data covering 6 months…(More)” See also: Transparency Centre.
Paper by Andrew Iliadis et al: “Several industry-specific metadata initiatives have historically facilitated structured data modeling for the web in domains such as commerce, publishing, social media, etc. The metadata vocabularies produced by these initiatives allow developers to ‘wrap’ information on the web to provide machine-readable signals for search engines, advertisers, and user-facing content on apps and websites, thus assisting with surfacing facts about people, places, and products. A universal iteration of such a project called Schema.org started in 2011, resulting from a partnership between Google, Microsoft, Yahoo, and Yandex to collaborate on a single structured data model across domains. Yet, few studies have explored the metadata vocabulary terms in this significant web resource. What terms are included, upon what subject domains do they focus, and how does Schema.org represent knowledge in its conceptual model? This paper presents findings from our extraction and analysis of the documented release history and complete hierarchy on Schema.org’s developer pages. We provide a semantic network visualization of Schema.org, including an analysis of its modularity and domains, and discuss its global significance concerning fact-checking and COVID-19. We end by theorizing Schema.org as a gatekeeper of data on the web that authors vocabulary that everyday web users encounter in their searches..(More)”.
Essay by Dilip Soman, and Bing Feng: “Over the past few years, we have had the opportunity to work with over 20 behavioral units as part of our Behaviourally Informed Organizations partnership. While we as a field know a fair bit about what works for changing the behavior of stakeholders, what can we say about what works for creating thriving behavioral units within organizations?
Based on our research and hard-won experience working with a diverse set of behavioral units in government, business, and not-for-profit organizations, we have seen many success stories. But we have also seen our share of instances where the units wished they had done things differently, units with promising pilots that didn’t scale well, units that tried to do everything for everyone, units that jumped to solutions too quickly, units too fixated on one methodology, and units too quick to dispense with advice without thinking through the context in which it will be used.
We’ve outlined six prescriptions that we think are critical to developing a successful behavioral unit—three don’ts and three dos. We hope the advice helps new and existing behavioral units find their path to success.
Prescription 1: Don’t anchor on solutions too soon
Many potential partners approach behavioral units with a preconceived notion of the outcome they want to find. For instance, we have been approached by partners asking us to validate their belief that an app, a website redesign, a new communication program, or a text messaging strategy will be the answer to their behavior change challenge. It is tempting to approach a problem with a concrete solution in mind because it can create the illusion of efficiency.
However, it has been our experience that anchoring on a solution constrains thinking and diverts attention to an aspect of the problem that might not be central to the issue.
For example, in a project one of us (Dilip) was involved in, the team had determined, very early on, that the most efficient and scalable way of delivering their interventions would be through a smartphone app. After extensive investments in developing, piloting, and testing an app, they realized that it didn’t work as expected. In hindsight, they realized that for the intervention to be successful, the recipient needed to pay a certain level of attention, something for which the app did not allow. The team made the mistake of anchoring too soon on a solution…(More)”.
Article by Andràs Szörényi and Pauline Leroy: Cities and their networks have risen on the international scene in the past decades as urban populations have increased dramatically. Cities have become more vocal on issues such as climate change, migration, and international conflict, as these challenges are increasingly impacting urban areas.
What’s more, innovative solutions to these problems are being invented in cities. And yet, despite their outsized contribution to the global economy and social development, cities have very few opportunities to engage in global decision-making and governance. They are not recognized stakeholders at the United Nations, and mayors are rarely afforded an international stage.
The Geneva Cities Hub – established in 2020 by the City and Canton of Geneva, with the support of the Swiss Confederation – enables cities and local governments to connect with Geneva-based international actors and amplify their voices.
Acknowledging cities as international actors is not just a good thing to do; it’s critical to developing policies that stand a chance of implementation.
When goals are announced and solutions are devised without the input of those in charge of implementation, unanticipated challenges inevitably arise. In short, including cities is critical to ensuring that decisions are practicable.
The Geneva Cities Hub has thus been empowered to facilitate the participation of cities in relevant multilateral processes in the Swiss city and beyond. We follow several of those and identify where the contribution of cities is relevant.
How cities can play a key role in multilateralism. Image: Geneva Cities Hub
We then work with states and international organizations to open these processes up and liaise with local governments to support their engagement…(More)”.
Article by Max Roser: “The big visualization offers a long-term perspective on the history of technology.
The timeline begins at the center of the spiral. The first use of stone tools, 3.4 million years ago, marks the beginning of this history of technology. Each turn of the spiral then represents 200,000 years of history. It took 2.4 million years – 12 turns of the spiral – for our ancestors to control fire and use it for cooking.3
To be able to visualize the inventions in the more recent past – the last 12,000 years – I had to unroll the spiral. I needed more space to be able to show when agriculture, writing, and the wheel were invented. During this period, technological change was faster, but it was still relatively slow: several thousand years passed between each of these three inventions.
From 1800 onwards, I stretched out the timeline even further to show the many major inventions that rapidly followed one after the other.
The long-term perspective that this chart provides makes it clear just how unusually fast technological change is in our time.
You can use this visualization to see how technology developed in particular domains. Follow, for example, the history of communication: from writing, to paper, to the printing press, to the telegraph, the telephone, the radio, all the way to the Internet and smartphones.
Or follow the rapid development of human flight. In 1903, the Wright brothers took the first flight in human history (they were in the air for less than a minute), and just 66 years later, we landed on the moon. Many people saw both within their lifetimes: the first plane and the moon landing.
This large visualization also highlights the wide range of technology’s impact on our lives. It includes extraordinarily beneficial innovations, such as the vaccine that allowed humanity to eradicate smallpox, and it includes terrible innovations, like the nuclear bombs that endanger the lives of all of us.
What will the next decades bring?
The red timeline reaches up to the present and then continues in green into the future. Many children born today, even without any further increases in life expectancy, will live well into the 22nd century.
New vaccines, progress in clean, low-carbon energy, better cancer treatments – a range of future innovations could very much improve our living conditions and the environment around us. But, as I argue in a series of articles, there is one technology that could even more profoundly change our world: artificial intelligence (AI).
One reason why artificial intelligence is such an important innovation is that intelligence is the main driver of innovation itself. This fast-paced technological change could speed up even more if it’s not only driven by humanity’s intelligence, but artificial intelligence too. If this happens, the change that is currently stretched out over the course of decades might happen within very brief time spans of just a year. Possibly even faster.
I think AI technology could have a fundamentally transformative impact on our world. In many ways, it is already changing our world, as I documented in this companion article. As this technology is becoming more capable in the years and decades to come, it can give immense power to those who control it (and it poses the risk that it could escape our control entirely).
Such systems might seem hard to imagine today, but AI technology is advancing very fast. Many AI experts believe there is a real chance that human-level artificial intelligence will be developed within the next decades, as I documented in this article….(More)”.
Article by Cass R. Sunstein: “In some circles, there is a misconception that within government, the only or principal uses of behavioral science consist of efforts to nudge individual behavior (sometimes described, pejoratively and unfairly, as “tweaks”). Nothing could be further from the truth. Behavioral science has been used, and is being used, to help inform large-scale reforms, including mandates and bans directed at companies (as, for example, in the cases of fuel-economy mandates and energy efficiency mandates). Behavioral science has been used, and is being used, to help inform taxes and subsidies (as, for example, in the cases of cigarette taxes, taxes on sugar-sweetened beverages, and subsides for electric cars). Behavioral science has been used, and is being used, to help inform nudges imposed on companies (with such goals as reducing greenhouse gas emissions, improving occupational safety, and protecting personal privacy). Some important interventions are indeed aimed at individuals (as with fuel economy labels, nutrition labels, and calorie labels, and automatic enrollment in savings plans); sometimes such interventions have significant positive effects, and there is no evidence that they make more aggressive reforms less likely. It is preposterous to suggest that choice-preserving interventions, such as nudges, “crowd out” more aggressive approaches…(More)”.
