Tech Platforms and the Knowledge Problem

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Frank Pasquale at American Affairs: “Friedrich von Hayek, the preeminent theorist of laissez-faire, called the “knowledge problem” an insuperable barrier to central planning. Knowledge about the price of supplies and labor, and consumers’ ability and willingness to pay, is so scattered and protean that even the wisest authorities cannot access all of it. No person knows everything about how goods and services in an economy should be priced. No central decision-maker can grasp the idiosyncratic preferences, values, and purchasing power of millions of individuals. That kind of knowledge, Hayek said, is distributed.

In an era of artificial intelligence and mass surveillance, however, the possibility of central planning has reemerged—this time in the form of massive firms. Having logged and analyzed billions of transactions, Amazon knows intimate details about all its customers and suppliers. It can carefully calibrate screen displays to herd buyers toward certain products or shopping practices, or to copy sellers with its own, cheaper, in-house offerings. Mark Zuckerberg aspires to omniscience of consumer desires, by profiling nearly everyone on Facebook, Instagram, and WhatsApp, and then leveraging that data trove to track users across the web and into the real world (via mobile usage and device fingerprinting). You don’t even have to use any of those apps to end up in Facebook/Instagram/WhatsApp files—profiles can be assigned to you. Google’s “database of intentions” is legendary, and antitrust authorities around the world have looked with increasing alarm at its ability to squeeze out rivals from search results once it gains an interest in their lines of business. Google knows not merely what consumers are searching for, but also what other businesses are searching, buying, emailing, planning—a truly unparalleled matching of data-processing capacity to raw communication flows.

Nor is this logic limited to the online context. Concentration is paying dividends for the largest banks (widely assumed to be too big to fail), and major health insurers (now squeezing and expanding the medical supply chain like an accordion). Like the digital giants, these finance and insurance firms not only act as middlemen, taking a cut of transactions, but also aspire to capitalize on the knowledge they have gained from monitoring customers and providers in order to supplant them and directly provide services and investment. If it succeeds, the CVS-Aetna merger betokens intense corporate consolidations that will see more vertical integration of insurers, providers, and a baroque series of middlemen (from pharmaceutical benefit managers to group purchasing organizations) into gargantuan health providers. A CVS doctor may eventually refer a patient to a CVS hospital for a CVS surgery, to be followed up by home health care workers employed by CVS who bring CVS pharmaceuticals—allcovered by a CVS/Aetna insurance plan, which might penalize the patient for using any providers outside the CVS network. While such a panoptic firm may sound dystopian, it is a logical outgrowth of health services researchers’ enthusiasm for “integrated delivery systems,” which are supposed to provide “care coordination” and “wraparound services” more efficiently than America’s current, fragmented health care system.

The rise of powerful intermediaries like search engines and insurers may seem like the next logical step in the development of capitalism. But a growing chorus of critics questions the size and scope of leading firms in these fields. The Institute for Local Self-Reliance highlights Amazon’s manipulation of both law and contracts to accumulate unfair advantages. International antitrust authorities have taken Google down a peg, questioning the company’s aggressive use of its search engine and Android operating system to promote its own services (and demote rivals). They also question why Google and Facebook have for years been acquiring companies at a pace of more than two per month. Consumer advocates complain about manipulative advertising. Finance scholars lambaste megabanks for taking advantage of the implicit subsidies that too-big-to-fail status confers….(More)”.

How the Math Men Overthrew the Mad Men

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 in the New Yorker: “Once, Mad Men ruled advertising. They’ve now been eclipsed by Math Men—the engineers and data scientists whose province is machines, algorithms, pureed data, and artificial intelligence. Yet Math Men are beleaguered, as Mark Zuckerberg demonstrated when he humbled himself before Congress, in April. Math Men’s adoration of data—coupled with their truculence and an arrogant conviction that their “science” is nearly flawless—has aroused government anger, much as Microsoft did two decades ago.

The power of Math Men is awesome. Google and Facebook each has a market value exceeding the combined value of the six largest advertising and marketing holding companies. Together, they claim six out of every ten dollars spent on digital advertising, and nine out of ten new digital ad dollars. They have become more dominant in what is estimated to be an up to two-trillion-dollar annual global advertising and marketing business. Facebook alone generates more ad dollars than all of America’s newspapers, and Google has twice the ad revenues of Facebook.

In the advertising world, Big Data is the Holy Grail, because it enables marketers to target messages to individuals rather than general groups, creating what’s called addressable advertising. And only the digital giants possess state-of-the-art Big Data. “The game is no longer about sending you a mail order catalogue or even about targeting online advertising,” Shoshana Zuboff, a professor of business administration at the Harvard Business School, wrote on faz.net, in 2016. “The game is selling access to the real-time flow of your daily life—your reality—in order to directly influence and modify your behavior for profit.” Success at this “game” flows to those with the “ability to predict the future—specifically the future of behavior,” Zuboff writes. She dubs this “surveillance capitalism.”

However, to thrash just Facebook and Google is to miss the larger truth: everyone in advertising strives to eliminate risk by perfecting targeting data. Protecting privacy is not foremost among the concerns of marketers; protecting and expanding their business is. The business model adopted by ad agencies and their clients parallels Facebook and Google’s. Each aims to massage data to better identify potential customers. Each aims to influence consumer behavior. To appreciate how alike their aims are, sit in an agency or client marketing meeting and you will hear wails about Facebook and Google’s “walled garden,” their unwillingness to share data on their users. When Facebook or Google counter that they must protect “the privacy” of their users, advertisers cry foul: You’re using the data to target ads we paid for—why won’t you share it, so that we can use it in other ad campaigns?…(More)”

Open government – Open for business?

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Dieter Zinnbauer at OGP: “Many activities related to opening government have a demonstrated, empirical potential to create business value, foster broader economic opportunities, and promote a business climate for growth and dynamism. What’s more, opening government plays a highly relevant, if not essential, role for economic stewardship and for putting economies on sustainable, inclusive trajectories of good growth. These are the central insights from this scan of the empirical literature on the economic and business dimension of open government. More specifically, opening government is found to have created sizeable business opportunities, innovation impetus, and to a somewhat lesser extent, new jobs—particularly in the area of open data. A growing body of empirical evidence also suggests that opening government has helped countries attract investments and capital, boost trade, reduce red tape, and remove barriers to market entry, all pointing towards an enhanced business and investment climate. At least equally important, there is compelling evidence that opening government supports good growth by enabling the containment of some of the major negative side effects of economic growth, by improving the targeting and efficacy of inclusive economic policies and benefits schemes, and by making it easier for businesses to live up to some of their fundamental societal responsibilities. Overall, the research landscape on opening government and business and economy nexus is still rather fragmented, and there are many promising, feasible, and much-needed avenues for future investigations in this fast-moving area….(More)”.

Superminds: The Surprising Power of People and Computers Thinking Together

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Book by Thomas W. Malone: “If you’re like most people, you probably believe that humans are the most intelligent animals on our planet. But there’s another kind of entity that can be far smarter: groups of people. In this groundbreaking book, Thomas Malone, the founding director of the MIT Center for Collective Intelligence, shows how groups of people working together in superminds — like hierarchies, markets, democracies, and communities — have been responsible for almost all human achievements in business, government, science, and beyond. And these collectively intelligent human groups are about to get much smarter.

Using dozens of striking examples and case studies, Malone shows how computers can help create more intelligent superminds not just with artificial intelligence, but perhaps even more importantly with hyperconnectivity:  connecting humans to one another at massive scales and in rich new ways. Together, these changes will have far-reaching implications for everything from the way we buy groceries and plan business strategies to how we respond to climate change, and even for democracy itself. By understanding how these collectively intelligent groups work, we can learn how to harness their genius to achieve our human goals….(More)”.

New Zealand explores machine-readable laws to transform government

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Apolitical: “The team working to drive New Zealand’s government into the digital age believes that part of the problem is the ways that laws themselves are written. Earlier this year, over a three-week experiment, they’ve tested the theory by rewriting legislation itself as software code.…

The team in New Zealand, led by the government’s service innovations team LabPlus, has attempted to improve the interpretation of legislation and vastly ease the creation of digital services by rewriting legislation as code.

Legislation-as-code means taking the “rules” or components of legislation — its logic, requirements and exemptions — and laying them out programmatically so that it can be parsed by a machine. If law can be broken down by a machine, then anyone, even those who aren’t legally trained, can work with it. It helps to standardise the rules in a consistent language across an entire system, giving a view of services, compliance and all the different rules of government.

Over the course of three weeks the team in New Zealand rewrote two sets of legislation as software code: the Rates Rebate Act, a tax rebate designed to lower the costs of owning a home for people on low incomes, and the Holidays Act, which was enacted to grant each employee in New Zealand a guaranteed four weeks a year of holiday.

The way that both policies are written makes them difficult to interpret, and, consequently, deliver. They were written for a paper-based world, and require different service responses from distinct bodies within government based on what the legal status of the citizen using them is. For instance, the residents of retirement villages are eligible to rebates through the Rates Rebate Act, but access it via different people and provide different information than normal ratepayers.

The teams worked to rewrite the legislation, first as “pseudocode” — the rules behind the legislation in a logical chain — then as human-readable legislation and finally as software code, designed to make it far easier for public servants and the public to work out who was eligible for what outcome. In the end, the team had working code for how to digitally deliver two policies.

A step towards digital government

The implications of such techniques are significant. Firstly, machine-readable legislation could speed up interactions between government and business, sparing private organisations the costs in time and money they currently spend interpreting the laws they need to comply with.

If legislation changes, the machine can process it automatically and consistently, saving the cost of employing an expert, or a lawyer, to do this job.

More transformatively for policymaking itself, machine-readable legislation allows public servants to test the impact of policy before they implement it.

“What happens currently is that people design the policy up front and wait to see how it works when you eventually deploy it,” said Richard Pope, one of the original pioneers in the UK’s Government Digital Service (GDS) and the co-author of the UK’s digital service standard. “A better approach is to design the legislation in such a way that gives the teams that are making and delivering a service enough wiggle room to be able to test things.”…(More)”.

The promise and peril of military applications of artificial intelligence

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Michael C. Horowitz at the Bulletin of the Atomic Scientists: “Artificial intelligence (AI) is having a moment in the national security space. While the public may still equate the notion of artificial intelligence in the military context with the humanoid robots of the Terminatorfranchise, there has been a significant growth in discussions about the national security consequences of artificial intelligence. These discussions span academia, business, and governments, from Oxford philosopher Nick Bostrom’s concern about the existential risk to humanity posed by artificial intelligence to Tesla founder Elon Musk’s concern that artificial intelligence could trigger World War III to Vladimir Putin’s statement that leadership in AI will be essential to global power in the 21st century.

What does this really mean, especially when you move beyond the rhetoric of revolutionary change and think about the real world consequences of potential applications of artificial intelligence to militaries? Artificial intelligence is not a weapon. Instead, artificial intelligence, from a military perspective, is an enabler, much like electricity and the combustion engine. Thus, the effect of artificial intelligence on military power and international conflict will depend on particular applications of AI for militaries and policymakers. What follows are key issues for thinking about the military consequences of artificial intelligence, including principles for evaluating what artificial intelligence “is” and how it compares to technological changes in the past, what militaries might use artificial intelligence for, potential limitations to the use of artificial intelligence, and then the impact of AI military applications for international politics.

The potential promise of AI—including its ability to improve the speed and accuracy of everything from logistics to battlefield planning and to help improve human decision-making—is driving militaries around the world to accelerate their research into and development of AI applications. For the US military, AI offers a new avenue to sustain its military superiority while potentially reducing costs and risk to US soldiers. For others, especially Russia and China, AI offers something potentially even more valuable—the ability to disrupt US military superiority. National competition in AI leadership is as much or more an issue of economic competition and leadership than anything else, but the potential military impact is also clear. There is significant uncertainty about the pace and trajectory of artificial intelligence research, which means it is always possible that the promise of AI will turn into more hype than reality. Moreover, safety and reliability concerns could limit the ways that militaries choose to employ AI…(More)”,

Citizenship and democratic production

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Article by Mara Balestrini and Valeria Right in Open Democracy: “In the last decades we have seen how the concept of innovation has changed, as not only the ecosystem of innovation-producing agents, but also the ways in which innovation is produced have expanded. The concept of producer-innovation, for example, where companies innovate on the basis of self-generated ideas, has been superseded by the concept of user-innovation, where innovation originates from the observation of the consumers’ needs, and then by the concept of consumer-innovation, where consumers enhanced by the new technologies are themselves able to create their own products. Innovation-related business models have changed too. We now talk about not only patent-protected innovation, but also open innovation and even free innovation, where open knowledge sharing plays a key role.

A similar evolution has taken place in the field of the smart city. While the first smart city models prioritized technology left in the hands of experts as a key factor for solving urban problems, more recent initiatives such as Sharing City (Seoul), Co-city (Bologna), or Fab City (Barcelona) focus on citizen participation, open data economics and collaborative-distributed processes as catalysts for innovative solutions to urban challenges. These initiatives could prompt a new wave in the design of more inclusive and sustainable cities by challenging existing power structures, amplifying the range of solutions to urban problems and, possibly, creating value on a larger scale.

In a context of economic austerity and massive urbanization, public administrations are acknowledging the need to seek innovative alternatives to increasing urban demands. Meanwhile, citizens, harnessing the potential of technologies – many of them accessible through open licenses – are putting their creative capacity into practice and contributing to a wave of innovation that could reinvent even the most established sectors.

Contributive production

The virtuous combination of citizen participation and abilities, digital technologies, and open and collaborative strategies is catalyzing innovation in all areas. Citizen innovation encompasses everything, from work and housing to food and health. The scope of work, for example, is potentially affected by the new processes of manufacturing and production on an individual scale: citizens can now produce small and large objects (new capacity), thanks to easy access to new technologies such as 3D printers (new element); they can also take advantage of new intellectual property licenses by adapting innovations from others and freely sharing their own (new rule) in response to a wide range of needs.

Along these lines, between 2015 and 2016, the city of Bristol launched a citizen innovation program aimed at solving problems related to the state of rented homes, which produced solutions through citizen participation and the use of sensors and open data. Citizens designed and produced themselves temperature and humidity sensors – using open hardware (Raspberry Pi), 3D printers and laser cutters – to combat problems related to home damp. These sensors, placed in the homes, allowed to map the scale of the problem, to differentiate between condensation and humidity, and thus to understand if the problem was due to structural failures of the buildings or to bad habits of the tenants. Through the inclusion of affected citizens, the community felt empowered to contribute ideas towards solutions to its problems, together with the landlords and the City Council.

A similar process is currently being undertaken in Amsterdam, Barcelona and Pristina under the umbrella of the Making Sense Project. In this case, citizens affected by environmental issues are producing their own sensors and urban devices to collect open data about the city and organizing collective action and awareness interventions….

Digital social innovation is disrupting the field of health too. There are different manifestations of these processes. First, platforms such as DataDonors or PatientsLikeMe show that there is an increasing citizen participation in biomedical research through the donation of their own health data…. projects such as OpenCare in Milan and mobile applications like Good Sam show how citizens can organize themselves to provide medical services that otherwise would be very costly or at a scale and granularity that the public sector could hardly afford….

The production processes of these products and services force us to think about their political implications and the role of public institutions, as they question the cities’ existing participation and contribution rules. In times of sociopolitical turbulence and austerity plans such as these, there is a need to design and test new approaches to civic participation, production and management which can strengthen democracy, add value and take into account the aspirations, emotional intelligence and agency of both individuals and communities.

In order for the new wave of citizen production to generate social capital, inclusive innovation and well-being, it is necessary to ensure that all citizens, particularly those from less-represented communities, are empowered to contribute and participate in the design of cities-for-all. It is therefore essential to develop programs to increase citizen access to the new technologies and the acquisition of the knowhow and skills needed to use and transform them….(More)

This piece is an excerpt from an original article published as part of the eBook El ecosistema de la Democracia Abierta.

New Power

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Privacy and Freedom of Expression In the Age of Artificial Intelligence

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Joint Paper by Privacy International and ARTICLE 19: “Artificial Intelligence (AI) is part of our daily lives. This technology shapes how people access information, interact with devices, share personal information, and even understand foreign languages. It also transforms how individuals and groups can be tracked and identified, and dramatically alters what kinds of information can be gleaned about people from their data. AI has the potential to revolutionise societies in positive ways. However, as with any scientific or technological advancement, there is a real risk that the use of new tools by states or corporations will have a negative impact on human rights. While AI impacts a plethora of rights, ARTICLE 19 and Privacy International are particularly concerned about the impact it will have on the right to privacy and the right to freedom of expression and information. This scoping paper focuses on applications of ‘artificial narrow intelligence’: in particular, machine learning and its implications for human rights.

The aim of the paper is fourfold:

1. Present key technical definitions to clarify the debate;

2. Examine key ways in which AI impacts the right to freedom of expression and the right to privacy and outline key challenges;

3. Review the current landscape of AI governance, including various existing legal, technical, and corporate frameworks and industry-led AI initiatives that are relevant to freedom of expression and privacy; and

4. Provide initial suggestions for rights-based solutions which can be pursued by civil society organisations and other stakeholders in AI advocacy activities….(More)”.

China asserts firm grip on research data

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ScienceMag: “In a move few scientists anticipated, the Chinese government has decreed that all scientific data generated in China must be submitted to government-sanctioned data centers before appearing in publications. At the same time, the regulations, posted last week, call for open access and data sharing.

The possibly conflicting directives puzzle researchers, who note that the yet-to-be-established data centers will have latitude in interpreting the rules. Scientists in China can still share results with overseas collaborators, says Xie Xuemei, who specializes in innovation economics at Shanghai University. Xie also believes that the new requirements to register data with authorities before submitting papers to journals will not affect most research areas. Gaining approval could mean publishing delays, Xie says, but “it will not have a serious impact on scientific research.”

The new rules, issued by the powerful State Council, apply to all groups and individuals generating research data in China. The creation of a national data center will apparently fall to the science ministry, though other ministries and local governments are expected to create their own centers as well. Exempted from the call for open access and sharing are data involving state and business secrets, national security, “public interest,” and individual privacy… (More)”