Paper by Mikko Leino and Katariina Kulha: “Deliberative mini-publics have often been considered to be a potential way to promote future-oriented thinking. Still, thinking about the future can be hard as it can evoke negative emotions such as stress and anxiety. This article establishes why a more positive outlook towards the future can benefit long-term decision-making. Then, it explores whether and to what extent deliberative mini-publics can facilitate thinking about the future by moderating negative emotions and encouraging positive emotions. We analyzed an online mini-public held in the region of Satakunta, Finland, organized to involve the public in the drafting process of a regional plan extending until the year 2050. In addition to the standard practices related to mini-publics, the Citizens’ Assembly included an imaginary time travel exercise, Future Design, carried out with half of the participants. Our analysis makes use of both survey and qualitative data. We found that democratic deliberation can promote positive emotions, like hopefulness and compassion, and lessen negative emotions, such as fear and confusion, related to the future. There were, however, differences in how emotions developed in the various small groups. Interviews with participants shed further light onto how participants felt during the event and how their sentiments concerning the future changed…(More)”.
Why the future might not be where you think it is
Article by Ruth Ogden: “Imagine the future. Where is it for you? Do you see yourself striding towards it? Perhaps it’s behind you. Maybe it’s even above you.
And what about the past? Do you imagine looking over your shoulder to see it?
How you answer these questions will depend on who you are and where you come from. The way we picture the future is influenced by the culture we grow up in and the languages we are exposed to.
For many people who grew up in the UK, the US and much of Europe, the future is in front of them, and the past is behind them. People in these cultures typically perceive time as linear. They see themselves as continually moving towards the future because they cannot go back to the past.
In some other cultures, however, the location of the past and the future are inverted. The Aymara, a South American Indigenous group of people living in the Andes, conceptualise the future as behind them and the past in front of them.
Scientists discovered this by studying the gestures of the Aymara people during discussions of topics such as ancestors and traditions. The researchers noticed that when Aymara spoke about their ancestors, they were likely to gesture in front of themselves, indicating that the past was in front. However, when they were asked about a future event, their gesture seemed to indicate that the future was perceived as behind.
Analysis of how people write, speak and gesture about time suggests that the Aymara are not alone. Speakers of Darij, an Arabic dialect spoken in Morocco, also appear to imagine the past as in front and the future behind. As do some Vietnamese speakers.
The future doesn’t always have to be behind or in front of us. There is evidence that some Mandarin speakers represent the future as down and the past as up. These differences suggest that there is no universal location for the past, present and future. Instead, people construct these representations based on their upbringing and surroundings.
Culture doesn’t just influence where we see the position of the future. It also influences how we see ourselves getting there…(More)”.
The State of Open Data 2023
Report by Springer Nature, Digital Science and Figshare: “The 2023 survey showed that the key motivations for researchers to share their data remain very similar to previous years, with full citation of research papers or a data citation ranking highly. 89% of respondents also said they make their data available publicly, however almost three quarters of respondents had never received support with planning, managing or sharing research data.
One size does not fit all: Variations in responses from different areas of expertise and geographies highlight a need for a more nuanced approach to research data management support globally. For example, 64% of respondents supported the idea of a national mandate for making research data openly available, with Indian and German respondents more likely to support this idea (both 71%).
Credit is an ongoing issue: For eight years running, our survey has revealed a recurring concern among researchers: the perception that they don’t receive sufficient recognition for openly sharing their data. 60% of respondents said they receive too little credit for sharing their data.
AI awareness hasn’t translated to action: For the first time, this year we asked survey respondents to indicate if they were using ChatGPT or similar AI tools for data collection, data processing and metadata collection. The most common response to all three questions was ‘I’m aware of these tools but haven’t considered it.’..(More)”.
Data Governance and Privacy Challenges in the Digital Healthcare Revolution
Paper by Nargiz Kazimova: “The onset of the COVID-19 pandemic has catalyzed an imperative for digital transformation in the healthcare sector. This study investigates the accelerated shift towards a digitally-enhanced healthcare delivery system, advocating for the widespread adoption of telemedicine and the relaxation of regulatory barriers. The paper also scrutinizes the burgeoning use of electronic health records, wearable devices, artificial intelligence, and machine learning, and how these technologies offer promising avenues for improving patient care and medical outcomes. Despite the advancements, the rapid digital integration raises significant privacy and security concerns. The stigma associated with certain illnesses and potential discrimination presents serious challenges that digital healthcare innovations can exacerbate.
This research underscores the criticality of stringent data governance to safeguard personal health information in the face of growing digitalization. The analysis begins with an exploration of the data governance role in optimizing healthcare outcomes and preserving privacy, followed by an assessment of the breadth and depth of health data proliferation. The paper subsequently navigates the complex legal and ethical terrain, contrasting HIPAA and GDPR frameworks to underline the current regulatory challenges.
A comprehensive set of strategic recommendations is provided for reinforcing data governance and enhancing privacy protection in healthcare. The author advises on updating legal provisions to match the dynamic healthcare environment, widening the scope of privacy laws, and improving the transparency of data-sharing practices. The establishment of ethical guidelines for the collection and use of health data is also recommended, focusing on explicit consent, decision-making transparency, harm accountability, maintenance of data anonymity, and the mitigation of biases in datasets.
Moreover, the study advocates for stronger transparency in data sharing with clear communication on data use, rigorous internal and external audit mechanisms, and informed consent processes. The conclusion calls for increased collaboration between healthcare providers, patients, administrative staff, ethicists, regulators, and technology companies to create governance models that reconcile patient rights with the expansive use of health data. The paper culminates in a call to action for a balanced approach to privacy and innovation in the data-driven era of healthcare…(More)”.
The AI regulations that aren’t being talked about
Article by Deloitte: “…But our research shows that this focus may be overlooking some of the most important tools already on the books. Of the 1,600+ policies we analyzed, only 11% were focused on regulating AI-adjacent issues like data privacy, cybersecurity, intellectual property, and so on (Figure 5). Even when limiting the search to only regulations, 60% were focused directly on AI and only 40% on AI-adjacent issues (Figure 5). For example, several countries have data protection agencies with regulatory powers to help protect citizens’ data privacy. But while these agencies may not have AI or machine learning named specifically in their charters, the importance of data in training and using AI models makes them an important AI-adjacent tool.
This can be problematic because directly regulating a fast-moving technology like AI can be difficult. Take the hypothetical example of removing bias from home loan decisions. Regulators could accomplish this goal by mandating that AI should have certain types of training data to ensure that the models are representative and will not produce biased results, but such an approach can become outdated when new methods of training AI models emerge. Given the diversity of different types of AI models already in use, from recurrent neural networks to generative pretrained transformers to generative adversarial networks and more, finding a single set of rules that can deliver what the public desires both now, and in the future, may be a challenge…(More)”.
Managing smart city governance – A playbook for local and regional governments
Report by UN Habitat” “This playbook and its recommendations are primarily aimed at municipal governments and their political leaders, local administrators, and public officials who are involved in smart city initiatives. The recommendations, which are delineated in the subsequent sections of this playbook, are intended to help develop more effective, inclusive, and sustainable governance practices for urban digital transformations. The guidance offered on these pages could also be useful for national agencies, private companies, non-governmental organizations, and all stakeholders committed to promoting the sustainable development of urban communities through the implementation of smart city initiatives…(More)”.
Despite Its Problems, Network Technology Can Help Renew Democracy
Essay by Daniel Araya: “The impact of digital technologies on contemporary economic and social development has been nothing short of revolutionary. The rise of the internet has transformed the way we share content, buy and sell goods, and manage our institutions. But while the hope of the internet has been its capacity to expand human connection and bring people together, the reality has often been something else entirely.
When social media networks first emerged about a decade ago, they were hailed as “technologies of liberation” with the capacity to spread democracy. While these social networks have undeniably democratized access to information, they have also helped to stimulate social and political fragmentation, eroding the discursive fibres that hold democracies together.
Prior to the internet, news and media were the domain of professional journalists, overseen by powerful experts, and shaped by gatekeepers. However, in the age of the internet, platforms circumvent the need for gatekeepers altogether. Bypassing the centralized distribution channels that have served as a foundation to mass industrial societies, social networks have begun reshaping the way democratic societies build consensus. Given the importance of discourse to democratic self-government, concern is growing that democracy is failing…(More)”.
Cities are ramping up to make the most of generative AI
Blog by Citylab: “Generative artificial intelligence promises to transform the way we work, and city leaders are taking note. According to a recent survey by Bloomberg Philanthropies in partnership with the Centre for Public Impact, the vast majority of mayors (96 percent) are interested in how they can use generative AI tools like ChatGPT—which rely on machine learning to identify patterns in data and create, or generate, new content after being fed prompts—to improve local government. Of those cities surveyed, 69 percent report that they are already exploring or testing the technology. Specifically, they’re interested in how it can help them more quickly and successfully address emerging challenges with traffic and transportation, infrastructure, public safety, climate, education, and more.
Yet even as a majority of city leaders surveyed are exploring generative AI’s potential, only a small fraction of them (2 percent) are actively deploying the technology. They indicated there are a number of issues getting in the way of broader implementation, including a lack of technical expertise, budgetary constraints, and ethical considerations like security, privacy, and transparency…(More)”.
Unlocking the Potential: The Call for an International Decade of Data
Working Paper by Stefaan Verhulst : “The goal of this working paper is to reiterate the central importance of data – to Artificial Intelligence (AI) in particular, but more generally to the landscape of digital technology.
What follows serves as a clarion call to the global community to prioritize and advance data as the bedrock for social and economic development, especially for the UN’s Sustainable Development Goals. It begins by recognizing the existence of significant remaining challenges related to data; encompassing issues of accessibility, distribution, divides, and asymmetries. In light of these challenges, and as we propel ourselves into an era increasingly dominated by AI and AI-related innovation, the paper argues that establishing a more robust foundation for the stewardship of data is critical; a foundation that, for instance, embodies inclusivity, self-determination, and responsibility.
Finally, the paper advocates for the creation of an International Decade of Data (IDD), an initiative aimed at solidifying this foundation globally and advancing our collective efforts towards data-driven progress.
Download ‘Unlocking the Potential: The Call for an International Decade of Data’ here. “
New Tools to Guide Data Sharing Agreements
Article by Andrew J. Zahuranec, Stefaan Verhulst, and Hannah Chafetz: “The process of forming a data-sharing agreement is not easy. The process involves figuring out incentives, evaluating the degree to which others are willing and able to collaborate, and defining the specific conduct that is and is not allowed. Even under the best of circumstances, these steps can be costly and time-consuming.
Today, the Open Data Policy Lab took a step to help data practitioners control these costs. “Moving from Idea to Practice: Three Resources to Streamline the Creation of Data Sharing Agreements” provides data practitioners with three resources meant to support them throughout the process of developing an agreement. These include:
- A Guide to Principled Data Sharing Agreement Negotiation by Design: A document outlining the different principles that a data practitioner might seek to uphold while negotiating an agreement;
- The Contractual Wheel of Data Collaboration 2.0: A listing of the different kinds of data sharing agreement provisions that a data practitioner might include in an agreement;
- A Readiness Matrix for Data Sharing Agreements: A form to evaluate the degree to which a partner can participate in a data-sharing agreement.
The resources are a result of a series of Open Data Action Labs, an initiative from the Open Data Policy Lab to define new strategies and tools that can help organizations resolve policy challenges they face. The Action Labs are built around a series of workshops (called “studios”) which given experts and stakeholders an opportunity to define the problems facing them and then ideate possible solutions in a collaborative setting. In February and March 2023, the Open Data Policy Lab and Trust Relay co-hosted conversations with experts in law, data, and smart cities on the challenge of forming a data sharing agreement. Find all the resources here.”