Stefaan Verhulst
Essay by Alex Murrell: “Marketers are prone to a prediction.
You’ll find them in the annual tirade of trend decks. In the PowerPoint projections of self-proclaimed prophets. In the feeds of forecasters and futurists. They crop up on every conference stage. They make their mark on every marketing magazine. And they work their way into every white paper.
To understand the extent of our forecasting fascination, I analysed the websites of three management consultancies looking for predictions with time frames ranging from 2025 to 2050. Whilst one prediction may be published multiple times, the size of the numbers still shocked me. Deloitte’s site makes 6904 predictions. McKinsey & Company make 4296. And Boston Consulting Group, 3679.
In total, these three companies’ websites include just shy of 15,000 predictions stretching out over the next 30 years.
But it doesn’t stop there.
My analysis finished in the year 2050 not because the predictions came to an end but because my enthusiasm did.
Search the sites and you’ll find forecasts stretching all the way to the year 2100. We’re still finding our feet in this century but some, it seems, already understand the next.
I believe the vast majority of these to be not forecasts but fantasies. Snake oil dressed up as science. Fiction masquerading as fact.
This article assesses how predictions have performed in five fields. It argues that poor projections have propagated throughout our society and proliferated throughout our industry. It argues that our fixation with forecasts is fundamentally flawed.
So instead of focussing on the future, let’s take a moment to look at the predictions of the past. Let’s see how our projections panned out….
Viewed through the lens of Tetlock, it becomes clear that the 15,000 predictions with which I began this article are not forecasts but fantasies.
The projections look precise. They sound scientific. But these forecasts are nothing more than delusions with decimal places. Snake oil dressed up as statistics. Fiction masquerading as fact. They provide a feeling of certainty but they deliver anything but.
In his 1998 book The Fortune Sellers, the business writer William A. Sherden quantified our consensual hallucination:
“Each year the prediction industry showers us with $200 billion in (mostly erroneous) information. The forecasting track records for all types of experts are universally poor, whether we consider scientifically oriented professionals, such as economists, demographers, meteorologists, and seismologists, or psychic and astrological forecasters whose names are household words.”
The comparison between professional predictors and fortune tellers is apt.
From tarot cards to tea leaves, palmistry to pyromancy, clear visions of cloudy futures have always been sold to susceptible audiences.
Today, marketers are one such audience.
It’s time we opened our eyes….(More)”.
Resource by All Tech Is Human: “How do you get involved in the growing Responsible Tech field? This guide is a comprehensive look at the vibrant Responsible Tech ecosystem. Aimed at college students, grad students, and young professionals, the “Responsible Tech Guide” is a mix of advice, career profiles, education journeys, and organizations in the space. Developed by All Tech Is Human, an organization committed to informing & inspiring the next generation of responsible technologists & changemakers….(More)”.
Essay by Nick Martin: “As the world struggles to achieve the UN’s Sustainable Development Goals (SDGs), the need for reliable data to track our progress is more important than ever. Government, civil society, and private sector organizations all play a role in producing, sharing, and using this data, but their information-gathering and -analysis efforts have been able to shed light on only 68 percent of the SDG indicators so far, according to a 2019 UN study.
To help fill the gap, the data science for social good (DSSG) movement has for years been making datasets about important social issues—such as health care infrastructure, school enrollment, air quality, and business registrations—available to trusted organizations or the public. Large tech companies such as Facebook, Google, Amazon, and others have recently begun to embrace the DSSG movement. Spurred on by advances in the field, the Development Data Partnership, the World Economic Forum’s 2030Vision consortium, and Data Collaboratives, they’re offering information about social media users’ mobility during COVID-19, cloud computing infrastructure to help nonprofits analyze large datasets, and other important tools and services.
But sharing data resources doesn’t mean they’ll be used effectively, if at all, to advance social impact. High-impact results require recipients of data assistance to inhabit a robust, holistic data ecosystem that includes assets like policies for safely handling data and the skills to analyze it. As tech firms become increasingly involved with using data and data science to help achieve the SDGs, it’s important that they understand the possibilities and limitations of the nonprofits and other civil society organizations they’re working with. Without a firm grasp on the data ecosystems of their partners, all the technical wizardry in the world may be for naught.
Companies must ask questions such as: What incentives or disincentives are in place for nonprofits to experiment with data science in their work? What gaps remain between what nonprofits or data scientists need and the resources funders provide? What skills must be developed? To help find answers, TechChange, an organization dedicated to using technology for social good, partnered with Project17, Facebook’s partnerships-led initiative to accelerate progress on the SDGs. Over the past six months, the team led interviews with top figures in the DSSG community from industry, academia, and the public sector. The 14 experts shared numerous insights into using data and data science to advance social good and the SDGs. Four takeaways emerged from our conversations and research…(More)”.
Book by Sinan Aral on “How Social Media Disrupts Our Elections, Our Economy, and Our Health–and How We Must Adapt”: “Drawing on two decades of his own research and business experience, Aral goes under the hood of the biggest, most powerful social networks to tackle the critical question of just how much social media actually shapes our choices, for better or worse. Aral shows how the tech behind social media offers the same set of behavior-influencing levers to both Russian hackers and brand marketers—to everyone who hopes to change the way we think and act—which is why its consequences affect everything from elections to business, dating to health. Along the way, he covers a wide array of topics, including how network effects fuel Twitter’s and Facebook’s massive growth to the neuroscience of how social media affects our brains, the real impact of fake news, the power of social ratings, and the effect of social media on our kids.
In mapping out strategies for being more thoughtful consumers of social media, The Hype Machine offers the definitive guide to understanding and harnessing for good the technology that has redefined our world overnight…(More)”.
Book by Jill Lepore: “The Simulmatics Corporation, launched during the Cold War, mined data, targeted voters, manipulated consumers, destabilized politics, and disordered knowledge—decades before Facebook, Google, and Cambridge Analytica. Jill Lepore, best-selling author of These Truths, came across the company’s papers in MIT’s archives and set out to tell this forgotten history, the long-lost backstory to the methods, and the arrogance, of Silicon Valley.
Founded in 1959 by some of the nation’s leading social scientists—“the best and the brightest, fatally brilliant, Icaruses with wings of feathers and wax, flying to the sun”—Simulmatics proposed to predict and manipulate the future by way of the computer simulation of human behavior. In summers, with their wives and children in tow, the company’s scientists met on the beach in Long Island under a geodesic, honeycombed dome, where they built a “People Machine” that aimed to model everything from buying a dishwasher to counterinsurgency to casting a vote. Deploying their “People Machine” from New York, Washington, Cambridge, and even Saigon, Simulmatics’ clients included the John F. Kennedy presidential campaign, the New York Times, the Department of Defense, and dozens of major manufacturers: Simulmatics had a hand in everything from political races to the Vietnam War to the Johnson administration’s ill-fated attempt to predict race riots. The company’s collapse was almost as rapid as its ascent, a collapse that involved failed marriages, a suspicious death, and bankruptcy. Exposed for false claims, and even accused of war crimes, it closed its doors in 1970 and all but vanished. Until Lepore came across the records of its remains.
The scientists of Simulmatics believed they had invented “the A-bomb of the social sciences.” They did not predict that it would take decades to detonate, like a long-buried grenade. But, in the early years of the twenty-first century, that bomb did detonate, creating a world in which corporations collect data and model behavior and target messages about the most ordinary of decisions, leaving people all over the world, long before the global pandemic, crushed by feelings of helplessness. This history has a past; If Then is its cautionary tale….(More)”.
Viewpoint by Elad Yom-Tov and Yuval Cherlow: “Recent research has shown the efficacy of screening for serious medical conditions from data collected while people interact with online services. In particular, queries to search engines and the interactions with them were shown to be advantageous for screening a range of conditions including diabetes, several forms of cancer, eating disorders, and depression. These screening abilities offer unique advantages in that they can serve a broad strata of the society, including people in underserved populations and in countries with poor access to medical services. However, these advantages need to be balanced against the potential harm to privacy, autonomy, and nonmaleficence, which are recognized as the cornerstones of ethical medical care. Here, we discuss these opportunities and challenges, both when collecting data to develop online screening services and when deploying them. We offer several solutions that balance the advantages of these services with the ethical challenges they pose….(More)”.
Article by Abhishek Gupta and Victoria Heath: “International organizations and corporations are racing to develop global guidelines for the ethical use of artificial intelligence. Declarations, manifestos, and recommendations are flooding the internet. But these efforts will be futile if they fail to account for the cultural and regional contexts in which AI operates.
AI systems have repeatedly been shown to cause problems that disproportionately affect marginalized groups while benefiting a privileged few. The global AI ethics efforts under way today—of which there are dozens—aim to help everyone benefit from this technology, and to prevent it from causing harm. Generally speaking, they do this by creating guidelines and principles for developers, funders, and regulators to follow. They might, for example, recommend routine internal audits or require protections for users’ personally identifiable information.
We believe these groups are well-intentioned and are doing worthwhile work. The AI community should, indeed, agree on a set of international definitions and concepts for ethical AI. But without more geographic representation, they’ll produce a global vision for AI ethics that reflects the perspectives of people in only a few regions of the world, particularly North America and northwestern Europe.
This work is not easy or straightforward. “Fairness,” “privacy,” and “bias” mean different things (pdf) in different places. People also have disparate expectations of these concepts depending on their own political, social, and economic realities. The challenges and risks posed by AI also differ depending on one’s locale.
If organizations working on global AI ethics fail to acknowledge this, they risk developing standards that are, at best, meaningless and ineffective across all the world’s regions. At worst, these flawed standards will lead to more AI systems and tools that perpetuate existing biases and are insensitive to local cultures….(More)”.
Paper by Tiffany C. Li: “The COVID-19 pandemic has caused millions of deaths and disastrous consequences around the world, with lasting repercussions for every field of law, including privacy and technology. The unique characteristics of this pandemic have precipitated an increase in use of new technologies, including remote communications platforms, healthcare robots, and medical AI. Public and private actors are using new technologies, like heat sensing, and technologically-influenced programs, like contact tracing, alike in response, leading to a rise in government and corporate surveillance in sectors like healthcare, employment, education, and commerce. Advocates have raised the alarm for privacy and civil liberties violations, but the emergency nature of the pandemic has drowned out many concerns.
This Article is the first comprehensive account of privacy impacts related to technology and public health responses to the COVID-19 crisis. Many have written on the general need for better health privacy protections, education privacy protections, consumer privacy protections, and protections against government and corporate surveillance. However, this Article is the first comprehensive article to examine these problems of privacy and technology specifically in light of the pandemic, arguing that the lens of the pandemic exposes the need for both widescale and small-scale reform of privacy law. This Article approaches these problems with a focus on technical realities and social salience, and with a critical awareness of digital and political inequities, crafting normative recommendations with these concepts in mind.
Understanding privacy in this time of pandemic is critical for law and policymaking in the near future and for the long-term goals of creating a future society that protects both civil liberties and public health. It is also important to create a contemporary scholarly understanding of privacy in pandemic at this moment in time, as a matter of historical record. By examining privacy in pandemic, in the midst of pandemic, this Article seeks to create a holistic scholarly foundation for future work on privacy, technology, public health, and legal responses to global crises….(More)”
Paper by Primavera De Filippi, Morshed Mannan and Wessel Reijers: “Blockchain technology was created as a response to the trust crisis that swept the world in the wake of the 2008 financial crisis. Bitcoin and other blockchain-based systems were presented as a “trustless” alternative to existing financial institutions and even governments. Yet, while the trustless nature of blockchain technology has been heavily questioned, little research has been done as to what blockchain technologies actually bring to the table in place of trust. This article draws from the extensive academic discussion on the concepts of “trust” and “confidence” to argue that blockchain technology is not a ‘trustless technology’ but rather a ‘confidence machine’. First, the article provides a review of the multifaceted conceptualisations of trust and confidence, and the relationship between these two concepts. Second, the claim is made that blockchain technology relies on cryptographic rules, mathematics, and game-theoretical incentives in order to increase confidence in the operations of a computational system. Yet, such an increase in confidence ultimately relies on the proper operation and governance of the underlying blockchain-based network, which requires trusting a variety of actors. Third, the article turns to legal, constitutional and polycentric governance theory to explore the governance challenges of blockchain-based systems, in light of the tension between procedural confidence and trust….(More)”
Paper by Tamara Ehs, and Monika Mokre: “The yellow vest movement started in November 2018 and has formed the longest protest movement in France since 1945. The movement provoked different reactions of the French government—on the one hand, violence and repression; on the other hand, concessions. One of them was to provide a possibility for citizens’ participation by organizing the so-called “Grand Débat.” It was clear to all observers that this was less an attempt to further democracy in France than to calm down the protests of the yellow vests. Thus, it seemed doubtful from the beginning whether this form of participatory democracy could be understood as a real form of citizens’ deliberation, and in fact, several shortcomings with regard to procedure and participation were pointed out by theorists of deliberative democracy. The aim of this article is to analyze the Grand Débat with regard to its deliberative qualities and shortcomings….(More)”.