Future of Professionals

Curated on Posted on by Stefaan Verhulst

Report by Thomson Reuters: “First, the productivity benefits we have been promised are now becoming more apparent. As AI adoption has become widespread, professionals can more tangibly tell us about how they will use this transformative technology and the greater efficiency and value it will provide. The most common use cases for AI-powered technology thus far include drafting documents, summarizing information, and performing basic research. Second, there’s a tremendous sense of excitement about the value that new AI-powered technology can bring to the day-to-day lives of the professionals we surveyed. While more than half of professionals said they’re most excited about the benefits that new AI-powered technologies can bring in terms of time-savings, nearly 40% said the new value that will be brought is what excites them the most.

This report highlights how AI could free up that precious commodity of time. As with the adoption of all new technology, change appears moderate and the impact incremental. And yet, within the year, our respondents predicted that for professionals, AI could free up as much as four hours a week. What will they do with 200 extra hours of time a year? They might reinvest that time in strategic work, innovation, and professional development, which could help companies retain or advance their competitive advantage. Imagine the broader impact on the economy and GDP from this increased efficiency. For US lawyers alone, that is a combined 266 million hours of increased productivity. That could translate into $100,000 in new, billable time per lawyer each year, based on current average rates – with similar productivity gains projected across various professions. The time saved can also be reinvested in professional development, nurturing work-life balance, and focusing on wellness and mental health. Moreover, the economic and organizational benefits of these time-savings are substantial. They could lead to reduced operational costs and higher efficiency, while enabling organizations to redirect resources toward strategic initiatives, fostering growth and competitiveness.

Finally, it’s important to acknowledge there’s still a healthy amount of reticence among professionals to fully adopt AI. Respondents are concerned primarily with the accuracy of outputs, and almost two-thirds of respondents agreed that data security is a vital component of responsible use. These concerns aren’t trivial, and they warrant attention as we navigate this new era of technology. While AI can provide tremendous productivity benefits to professionals and generate greater value for businesses, that’s only possible if we build and use this technology responsibly.”…(More)”.

Democracy online: technologies for democratic deliberation

Curated on Posted on by Stefaan Verhulst

Paper by Adam Meylan-Stevenson, Ben Hawes, and Matt Ryan: “This paper explores the use of online tools to improve democratic participation and deliberation. These tools offer new opportunities for inclusive communication and networking, specifically targeting the participation of diverse groups in decision-making processes. It summarises recent research and published reports by users of these tools and categorises the tools according to functions and objectives. It also draws on testimony and experiences recorded in interviews with some users of these tools in public sector and civil society organisations internationally.


The objective is to introduce online deliberation tools to a wider audience, including benefits, limitations and potential disadvantages, in the immediate context of research on democratic deliberation. We identify limitations of tools and of the context and markets in which online deliberation tools are currently being developed. The paper suggests that fostering a collaborative approach among technology developers and democratic practitioners, might improve opportunities for funding and continual optimisation that have been used successfully in other online application sectors…(More)”.

Dada-Disinfo

Curated on Posted on by Stefaan Verhulst

Report by Mark Kaigwa et al: “The “Dada Disinfo: Technology-Facilitated Gender-Based Violence (TFGBV) Report,” prepared by Nendo and Pollicy, outlines the pervasive issue of TFGBV in Kenya’s vibrant but volatile social media ecosystem. The report draws on extensive research, including social media analytics, surveys, and in-depth interviews with content creators, to shed light on the manifestations, perpetrators, and impacts of TFGBV. The project, supported by USAID and conducted in collaboration with Pollicy, integrates advanced analytics to offer insights and potential solutions to mitigate online gender-based violence in Kenya…(More)”.

United Nations Global Principles for Information Integrity

Curated on Posted on by Stefaan Verhulst

United Nations: “Technological advances have revolutionized communications, connecting people on a previously unthinkable scale. They have supported communities in times of crisis, elevated marginalized voices and helped mobilize global movements for racial justice and gender equality.

Yet these same advances have enabled the spread of misinformation, disinformation and hate speech at an unprecedented volume, velocity and virality, risking the integrity of the information ecosystem.

New and escalating risks stemming from leaps in AI technologies have made strengthening information integrity one of the urgent tasks of our time.

This clear and present global threat demands coordinated international action.

The United Nations Global Principles for Information Integrity show us another future is possible…(More)”

Doing science backwards

Curated on Posted on by Stefaan Verhulst

Article by Stuart Ritchie: “…Usually, the process of publishing such a study would look like this: you run the study; you write it up as a paper; you submit it to a journal; the journal gets some other scientists to peer-review it; it gets published – or if it doesn’t, you either discard it, or send it off to a different journal and the whole process starts again.

That’s standard operating procedure. But it shouldn’t be. Think about the job of the peer-reviewer: when they start their work, they’re handed a full-fledged paper, reporting on a study and a statistical analysis that happened at some point in the past. It’s all now done and, if not fully dusted, then in a pretty final-looking form.

What can the reviewer do? They can check the analysis makes sense, sure; they can recommend new analyses are done; they can even, in extreme cases, make the original authors go off and collect some entirely new data in a further study – maybe the data the authors originally presented just aren’t convincing or don’t represent a proper test of the hypothesis.

Ronald Fisher described the study-first, review-later process in 1938:

To consult the statistician [or, in our case, peer-reviewer] after an experiment is finished is often merely to ask him to conduct a post mortem examination. He can perhaps say what the experiment died of.

Clearly this isn’t the optimal, most efficient way to do science. Why don’t we review the statistics and design of a study right at the beginning of the process, rather than at the end?

This is where Registered Reports come in. They’re a new (well, new-ish) way of publishing papers where, before you go to the lab, or wherever you’re collecting data, you write down your plan for your study and send it off for peer-review. The reviewers can then give you genuinely constructive criticism – you can literally construct your experiment differently depending on their suggestions. You build consensus—between you, the reviewers, and the journal editor—on the method of the study. And then, once everyone agrees on what a good study of this question would look like, you go off and do it. The key part is that, at this point, the journal agrees to publish your study, regardless of what the results might eventually look like…(More)”.

How the Rise of the Camera Launched a Fight to Protect Gilded Age Americans’ Privacy

Curated on Posted on by Stefaan Verhulst

Article by Sohini Desai: “In 1904, a widow named Elizabeth Peck had her portrait taken at a studio in a small Iowa town. The photographer sold the negatives to Duffy’s Pure Malt Whiskey, a company that avoided liquor taxes for years by falsely advertising its product as medicinal. Duffy’s ads claimed the fantastical: that it cured everything from influenza to consumption, that it was endorsed by clergymen, that it could help you live until the age of 106. The portrait of Peck ended up in one of these dubious ads, published in newspapers across the country alongside what appeared to be her unqualified praise: “After years of constant use of your Pure Malt Whiskey, both by myself and as given to patients in my capacity as nurse, I have no hesitation in recommending it.”

Duffy’s lies were numerous. Peck (misleadingly identified as “Mrs. A. Schuman”) was not a nurse, and she had not spent years constantly slinging back malt beverages. In fact, she fully abstained from alcohol. Peck never consented to the ad.

The camera’s first great age—which began in 1888 when George Eastman debuted the Kodak—is full of stories like this one. Beyond the wonders of a quickly developing art form and technology lay widespread lack of control over one’s own image, perverse incentives to make a quick buck, and generalized fear at the prospect of humiliation and the invasion of privacy…(More)”.

Enhancing human mobility research with open and standardized datasets

Curated on Posted on by Stefaan Verhulst

Article by Takahiro Yabe et al: “The proliferation of large-scale, passively collected location data from mobile devices has enabled researchers to gain valuable insights into various societal phenomena. In particular, research into the science of human mobility has become increasingly critical thanks to its interdisciplinary effects in various fields, including urban planning, transportation engineering, public health, disaster management, and economic analysis. Researchers in the computational social science, complex systems, and behavioral science communities have used such granular mobility data to uncover universal laws and theories governing individual and collective human behavior. Moreover, computer science researchers have focused on developing computational and machine learning models capable of predicting complex behavior patterns in urban environments. Prominent papers include pattern-based and deep learning approaches to next-location prediction and physics-inspired approaches to flow prediction and generation.

Regardless of the research problem of interest, human mobility datasets often come with substantial limitations. Existing publicly available datasets are often small, limited to specific transport modes, or geographically restricted, owing to the lack of open-source and large-scale human mobility datasets caused by privacy concerns…(More)”.

The Role of Open Data in Driving Sectoral Innovation and Global Economic Development

Curated on Posted on by Stefaan Verhulst

Paper by Olalekan Jamiu Okunleye: “This study assessed the transformative impact of implementing open data principles on fostering innovation across various sectors and enhancing global economic development. Using a comprehensive analysis of secondary data from government portals, industry reports, and global innovation indexes between 2015 to 2019, the research employed panel data regression, correlation analysis, and descriptive statistics to evaluate key relationships. The findings indicate that the availability of open data significantly increases innovation outputs, with robust statistical evidence showing positive correlations between open data sets and sector-specific innovation metrics such as patents filed, R&D expenditure, and the number of startups created. Greater interoperability of open data across international borders contributes to economic growth, particularly through international joint ventures. However, the lack of standardized data formats hampers cross-sector collaboration. Regions with well-established open data policies demonstrate faster technological advancements and economic development compared to regions without such policies. The study highlighted the critical importance of promoting open data initiatives, standardizing data formats, strengthening data governance frameworks, and investing in digital infrastructure and capacity building to optimize open data utilization and drive sustainable development…(More)”.

Searching for Safer, Healthier Digital Spaces

Curated on Posted on by Stefaan Verhulst

Report by Search for Common Ground (Search): “… has specialized in approaches that leverage media such as radio and television to reach target audiences. In recent years, the organization has been more intentional about digital and online spaces, delving deeper into the realm of digital peacebuilding. Search has since implemented a number of digital peacebuilding projects.

Search wanted to understand if and how its initiatives were able to catalyze constructive agency among social media users, away from a space of apathy, self-doubt, or fear to incite inclusion, belonging, empathy, mutual understanding, and trust. This report examines these hypotheses using primary data from former and current participants in Search’s digital peacebuilding initiatives…(More)”

Designing an Effective Governance Model for Data Collaboratives

Curated on Posted on by Stefaan Verhulst

Paper by Federico Bartolomucci & Francesco Leoni: “Data Collaboratives have gained traction as interorganizational partnerships centered on data exchange. They enhance the collective capacity of responding to contemporary societal challenges using data, while also providing participating organizations with innovation capabilities and reputational benefits. Unfortunately, data collaboratives often fail to advance beyond the pilot stage and are therefore limited in their capacity to deliver systemic change. The governance setting adopted by a data collaborative affects how it acts over the short and long term. We present a governance design model to develop context-dependent data collaboratives. Practitioners can use the proposed model and list of key reflective questions to evaluate the critical aspects of designing a governance model for their data collaboratives…(More)”.