When Ideology Drives Social Science

Curated on Posted on by Stefaan Verhulst

Article by Michael Jindra and Arthur Sakamoto: Last summer in these pages, Mordechai Levy-Eichel and Daniel Scheinerman uncovered a major flaw in Richard Jean So’s Redlining Culture: A Data History of Racial Inequality and Postwar Fiction, one that rendered the book’s conclusion null and void. Unfortunately, what they found was not an isolated incident. In complex areas like the study of racial inequality, a fundamentalism has taken hold that discourages sound methodology and the use of reliable evidence about the roots of social problems.

We are not talking about mere differences in interpretation of results, which are common. We are talking about mistakes so clear that they should cause research to be seriously questioned or even disregarded. A great deal of research — we will focus on examinations of Asian American class mobility — rigs its statistical methods in order to arrive at ideologically preferred conclusions.

Most sophisticated quantitative work in sociology involves multivariate research, often in a search for causes of social problems. This work might ask how a particular independent variable (e.g., education level) “causes” an outcome or dependent variable (e.g., income). Or it could study the reverse: How does parental income influence children’s education?

Human behavior is too complicated to be explained by only one variable, so social scientists typically try to “control” for various causes simultaneously. If you are trying to test for a particular cause, you want to isolate that cause and hold all other possible causes constant. One can control for a given variable using what is called multiple regression, a statistical tool that parcels out the separate net effects of several variables simultaneously.

If you want to determine whether income causes better education outcomes, you’d want to compare everyone from a two-parent family, since family status might be another causal factor, for instance. You’d also want to see the effect of family status by comparing everyone with similar incomes. And so on for other variables.

The problem is that there are potentially so many variables that a researcher inevitably leaves some out…(More)”.

The False Promise of ChatGPT

Curated on Posted on by Stefaan Verhulst

Article by Noam Chomsky: “…OpenAI’s ChatGPT, Google’s Bard and Microsoft’s Sydney are marvels of machine learning. Roughly speaking, they take huge amounts of data, search for patterns in it and become increasingly proficient at generating statistically probable outputs — such as seemingly humanlike language and thought. These programs have been hailed as the first glimmers on the horizon of artificial general intelligence — that long-prophesied moment when mechanical minds surpass human brains not only quantitatively in terms of processing speed and memory size but also qualitatively in terms of intellectual insight, artistic creativity and every other distinctively human faculty.

That day may come, but its dawn is not yet breaking, contrary to what can be read in hyperbolic headlines and reckoned by injudicious investments. The Borgesian revelation of understanding has not and will not — and, we submit, cannot — occur if machine learning programs like ChatGPT continue to dominate the field of A.I. However useful these programs may be in some narrow domains (they can be helpful in computer programming, for example, or in suggesting rhymes for light verse), we know from the science of linguistics and the philosophy of knowledge that they differ profoundly from how humans reason and use language. These differences place significant limitations on what these programs can do, encoding them with ineradicable defects.

It is at once comic and tragic, as Borges might have noted, that so much money and attention should be concentrated on so little a thing — something so trivial when contrasted with the human mind, which by dint of language, in the words of Wilhelm von Humboldt, can make “infinite use of finite means,” creating ideas and theories with universal reach…(More)”.

Innovation Power: Why Technology Will Define the Future of Geopolitics

Curated on Posted on by Stefaan Verhulst

Essay by Eric Schmidt: “When Russian forces marched on Kyiv in February 2022, few thought Ukraine could survive. Russia had more than twice as many soldiers as Ukraine. Its military budget was more than ten times as large. The U.S. intelligence community estimated that Kyiv would fall within one to two weeks at most.

Outgunned and outmanned, Ukraine turned to one area in which it held an advantage over the enemy: technology. Shortly after the invasion, the Ukrainian government uploaded all its critical data to the cloud, so that it could safeguard information and keep functioning even if Russian missiles turned its ministerial offices into rubble. The country’s Ministry of Digital Transformation, which Ukrainian President Volodymyr Zelensky had established just two years earlier, repurposed its e-government mobile app, Diia, for open-source intelligence collection, so that citizens could upload photos and videos of enemy military units. With their communications infrastructure in jeopardy, the Ukrainians turned to Starlink satellites and ground stations provided by SpaceX to stay connected. When Russia sent Iranian-made drones across the border, Ukraine acquired its own drones specially designed to intercept their attacks—while its military learned how to use unfamiliar weapons supplied by Western allies. In the cat-and-mouse game of innovation, Ukraine simply proved nimbler. And so what Russia had imagined would be a quick and easy invasion has turned out to be anything but.

Ukraine’s success can be credited in part to the resolve of the Ukrainian people, the weakness of the Russian military, and the strength of Western support. But it also owes to the defining new force of international politics: innovation power. Innovation power is the ability to invent, adopt, and adapt new technologies. It contributes to both hard and soft power. High-tech weapons systems increase military might, new platforms and the standards that govern them provide economic leverage, and cutting-edge research and technologies enhance global appeal. There is a long tradition of states harnessing innovation to project power abroad, but what has changed is the self-perpetuating nature of scientific advances. Developments in artificial intelligence in particular not only unlock new areas of scientific discovery; they also speed up that very process. Artificial intelligence supercharges the ability of scientists and engineers to discover ever more powerful technologies, fostering advances in artificial intelligence itself as well as in other fields—and reshaping the world in the process…(More)”.

Ten lessons for data sharing with a data commons

Curated on Posted on by Stefaan Verhulst

Article by Robert L. Grossman: “..Lesson 1. Build a commons for a specific community with a specific set of research challenges

Although there are a few data repositories that serve the general scientific community that have proved successful, in general data commons that target a specific user community have proven to be the most successful. The first lesson is to build a data commons for a specific research community that is struggling to answer specific research challenges with data. As a consequence, a data commons is a partnership between the data scientists developing and supporting the commons and the disciplinary scientists with the research challenges.

Lesson 2. Successful commons curate and harmonize the data

Successful commons curate and harmonize the data and produce data products of broad interest to the community. It’s time consuming, expensive, and labor intensive to curate and harmonize data, by much of the value of data commons is centralizing this work so that it can be done once instead of many times by each group that needs the data. These days, it is very easy to think of a data commons as a platform containing data, not spend the time curating or harmonizing it, and then be surprised that the data in the commons is not used more widely used and its impact is not as high as expected.

Lesson 3. It’s ultimately about the data and its value to generate new research discoveries

Despite the importance of a study, few scientists will try to replicate previously published studies. Instead, data is usually accessed if it can lead to a new high impact paper. For this reason, data commons play two different but related roles. First, they preserve data for reproducible science. This is a small fraction of the data access, but plays a critical role in reproducible science. Second, data commons make data available for new high value science.

Lesson 4. Reduce barriers to access to increase usage

A useful rule of thumb is that every barrier to data access cuts down access by a factor of 10. Common barriers that reduce use of a commons include: registration vs no-registration; open access vs controlled access; click through agreements vs signing of data usage agreements and approval by data access committees; license restrictions on the use of the data vs no license restrictions…(More)”.

Satellite data: The other type of smartphone data you might not know about

Curated on Posted on by Stefaan Verhulst

Article by Tommy Cooke et al: “Smartphones determine your location in several ways. The first way involves phones triangulating distances between cell towers or Wi-Fi routers.

The second way involves smartphones interacting with navigation satellites. When satellites pass overhead, they transmit signals to smartphones, which allows smartphones to calculate their own location. This process uses a specialized piece of hardware called the Global Navigation Satellite System (GNSS) chipset. Every smartphone has one.

When these GNSS chipsets calculate navigation satellite signals, they output data in two standardized formats (known as protocols or languages): the GNSS raw measurement protocol and the National Marine Electronics Association protocol (NMEA 0183).

GNSS raw measurements include data such as the distance between satellites and cellphones and measurements of the signal itself.

NMEA 0183 contains similar information to GNSS raw measurements, but also includes additional information such as satellite identification numbers, the number of satellites in a constellation, what country owns a satellite, and the position of a satellite.

NMEA 0183 was created and is governed by the NMEA, a not-for-profit lobby group that is also a marine electronics trade organization. The NMEA was formed at the 1957 New York Boat Show when boating equipment manufacturers decided to build stronger relationships within the electronic manufacturing industry.

In the decades since, the NMEA 0183 data standard has improved marine electronics communications and is now found on a wide variety of non-marine communications devices today, including smartphones…

It is difficult to know who has access to data produced by these protocols. Access to NMEA protocols is only available under licence to businesses for a fee.

GNSS raw measurements, on the other hand, are a universal standard and can be read by different devices in the same way without a license. In 2016, Google allowed industries to have open access to it to foster innovation around device tracking accuracy, precision, analytics about how we move in real-time, and predictions about our movements in the future.

While automated processes can quietly harvest location data — like when a French-based company extracted location data from Salaat First, a Muslim prayer app — these data don’t need to be taken directly from smartphones to be exploited.

Data can be modelled, experimented with, or emulated in licensed devices in labs for innovation and algorithmic development.

Satellite-driven raw measurements from our devices were used to power global surveillance networks like STRIKE3, a now defunct European-led initiative that monitored and reported perceived threats to navigation satellites…(More)”.

Elon Musk Has Broken Disaster-Response Twitter

Curated on Posted on by Stefaan Verhulst

Article by Juliette Kayyem: “For years, Twitter was at its best when bad things happened. Before Elon Musk bought it last fall, before it was overrun with scammy ads, before it amplified fake personas, and before its engineers were told to get more eyeballs on the owner’s tweets, Twitter was useful in saving lives during natural disasters and man-made crises. Emergency-management officials have used the platform to relate timely information to the public—when to evacuate during Hurricane Ian, in 2022; when to hide from a gunman during the Michigan State University shootings earlier this month—while simultaneously allowing members of the public to transmit real-time data. The platform didn’t just provide a valuable communications service; it changed the way emergency management functions.

That’s why Musk-era Twitter alarms so many people in my field. The platform has been downgraded in multiple ways: Service is glitchier; efforts to contain misleading information are patchier; the person at the top seems largely dismissive of outside input. But now that the platform has embedded itself so deeply in the disaster-response world, it’s difficult to replace. The rapidly deteriorating situation raises questions about platforms’ obligation to society—questions that prickly tech execs generally don’t want to consider…(More)”

The region that’s experimenting with government by lottery

Curated on Posted on by Stefaan Verhulst

Article by Hugh Pope: “If we are trying to fix our “broken politics”, is the solution really just another set of politicians? If the electoral system is at fault, might the process of government work better if it were run by a group of randomly selected citizens?

Liesa Scholzen is a politician whose constituents are the 70,000 German speakers on Belgium’s eastern border. People with an interest in new political systems are paying close attention to Scholzen’s hilltop parliament in Eupen, Ostbelgien. That’s because in 2021, as part of its Citizens’ Dialogue initiative, Ostbelgien inaugurated the world’s first official, permanent legislative body chosen not by votes, but by lottery. 

Scholzen’s visitors come from round the world to learn about this new process of sortition, but Scholzen herself mostly looked bemused by their enthusiasm. “I’m just a part-time politician. And I’m a citizen too!” she reminded her audience of around 50, who had come to hear her talk about the strange new politics.

Ostbelgien’s new system takes some getting used to. It’s named “The Citizens’ Dialogue” and is led by a standing council of citizens, drawn by lot. The 24-member council serves for 18 months, and they choose the topics which are then debated by separate Citizens’ Assemblies. These assemblies have 25-50 members, also chosen by lot, who make their recommendations following two to three days of deliberation. Members meet in the evening or at weekends, and receive expenses plus €50 to €95 (£44-£84) per session. All participants are chosen from the German-speaking community. 

So has it caught on? Ostbelgien’s Citizens’ Dialogue may be “well known internationally, but here some people don’t know it exists,” Scholzen explained to her visitors. “They haven’t had a real impact… When the first Citizens’ Assembly report came in, we told them: ‘You just can’t do it that way. It won’t work.’ So we just changed [some parts of] it… The Citizens’ Dialogue is still in its kinderschuhen, its ‘children’s shoes’.”

Indeed, it is only in the past decade that the worldwide movement for democracy by sortition began gaining momentum. Most of the 50 enthusiasts who gathered for an “autumn school” in Eupen, including myself, believe that it has the potential to break the logjam in governance caused by dysfunctional electoral systems. But progress has been slow…(More)”.

Seize the Future by Harnessing the Power of Data

Curated on Posted on by Stefaan Verhulst

Article by Kriss Deiglmeier: “Data is a form of power. And the sad reality is that power is being held increasingly by the commercial sector and not by organizations seeking to create a more just, sustainable, and prosperous world. A year into my tenure as the chief global impact officer at Splunk, I became consumed with the new era driven by data. Specifically, I was concerned with the emerging data divide, which I defined as “the disparity between the expanding use of data to create commercial value, and the comparatively weak use of data to solve social and environmental challenges.”2

We need to face the fact that the underlying foundation of society is shifting while the social sector is not. This foundational change is laid out in the new book coauthored by Eric Schmidt, Henry Kissinger, and Daniel Huttenlocker, The Age of AI. They make the case that we are moving into a coexistence between humanity and machines. From a historical context, the evolution of humans started in the age of faith that evolved into the age of reason. The future upon us now is the age of people and machines. The world around us will increasingly be full of intelligent systems that will be humanlike but not human. Society, especially the social sector, must get ahead of the implications of that and plan for both the good and bad impact it will have on society. After all, who better to look out for the “people” part of the “people and machines” than the human-centric social sector?

To effectively address the emerging data future, the social impact sector must build an entire impact data ecosystem for this moment in time—and the next moment in time. The way to do that is by investing in those areas where we currently lag the commercial sector. Consider the following gaps:

  • Nonprofits are ill-equipped with the financial and technical resources they need to make full use of data, often due to underfunding.
  • The sector’s technical and data talent is a desert compared to the commercial sector.
  • While the sector is rich with output and service-delivery data, that data is locked away or is unusable in its current form.
  • The sector lacks living data platforms (collaboratives and data refineries) that can make use of sector-wide data in a way that helps improve service delivery, maximize impact, and create radical innovation.

The harsh realities of the sector’s disparate data skills, infrastructure, and competencies show the dire current state. For the impact sector to transition to a place of power, it must jump without hesitation into the arena of the Data Age—and invest time, talent, and money in filling in these gaps…(More)”.

Design thinking was supposed to fix the world. Where did it go wrong?

Curated on Posted on by Stefaan Verhulst

Article by Rebecca Ackermann: “…But in recent years, for a number of reasons, the shine of design thinking has been wearing off. Critics have argued that its short-term focus on novel and naive ideas has resulted in unrealistic and ungrounded recommendations. And they have maintained that by centering designers—mainly practitioners of corporate design within agencies—it has reinforced existing inequities rather than challenging them. Years in, “innovation theater”— checking a series of boxes without implementing meaningful shifts—had become endemic in corporate settings, while a number of social-impact initiatives highlighted in case studies struggled to get beyond pilot projects. Meanwhile, the #MeToo and BLM movements, along with the political turmoil of the Trump administration, have demonstrated that many big problems are rooted in centuries of dark history, too deeply entrenched to be obliterated with a touch of design thinking’s magic wand. 

Today, innovation agencies and educational institutions still continue to sell design thinking to individuals, corporations, and organizations. In 2015, IDEO even created its own “online school,” IDEO U, with a bank of design thinking courses. But some groups—including the d.school and IDEO itself—are working to reform both its principles and its methodologies. These new efforts seek a set of design tools capable of equitably serving diverse communities and solving diverse problems well into the future. It’s a much more daunting—and crucial—task than design thinking’s original remit…(More)”.

A Happier Internet: Searching for creativity in a profoundly uncreative medium

Curated on Posted on by Stefaan Verhulst

Article by Jonathan D. Teubner: “Twitch is a social media platform where people can livestream themselves playing video games. Its streaming stars, who seem to dress mostly either in cosplay or for a day at Miami Beach, bring their fans directly into their homes and, in many cases, actual bedrooms. Twitch encourages its streaming stars to engage more personally with their followers. These “fans,” as they are called, can start to feel as though they have an actual relationship with the stars.

Connecting with others while playing video games apparently has its appeal, and monetary rewards. Top stars make as much as $120,000 per month. Twitch streamers with more modest followings can easily earn a living wage playing video games in full view of the world online. As one streaming star, Sweet Anita, told a New York Times reporter recently, “I laugh every day. I get paid to play video games. It’s a surreal world.”

Surreal doesn’t quite seem to capture it. Occasionally fans don’t see it merely for the money-making conceit that it is. Stalking is a common problem. One streamer known as DizzyKitten had the understandably alarming experience of one of her followers traveling from Washington State to her small town in Arkansas on the pretense that they were married. Others have received death threats against themselves and their families for considering moving onto a different platform. The online world rarely, if ever, stays online.

By now we are all accustomed to the problems presented by social media. The mental health maladies associated with heavy use can give one pause—depression, memory loss, sleeplessness. But perhaps the more disturbing consequences occur when social media erupts into our everyday lives: stalking, death threats, violence. This, too, is the world social media has wrought.

It’s become somewhat standard to say that Facebook, Twitter, Instagram, and smaller platforms like Twitch are a novum—something completely new our society must grapple with. Our best psychologists, neuroscientists, and epidemiologists are on the case. But as Kevin Driscoll charts in The Modem World, social media has a history. The premise behind his book is that this history is worth reconstructing, if for no other reason than that it discloses a different way to be online, one that is less corporate and more participatory….(More)”.