Mayor de Blasio Signs Executive Order to Establish Algorithms Management and Policy Officer

Curated on Posted on by Stefaan Verhulst

Press release: “Mayor Bill de Blasio today signed an Executive Order to establish an Algorithms Management and Policy Officer within the Mayor’s Office of Operations. The Officer will serve as a centralized resource on algorithm policy and develop guidelines and best practices to assist City agencies in their use of algorithms to make decisions. The new Officer will ensure relevant algorithms used by the City to deliver services promote equity, fairness and accountability. The creation of the position follows review of the recommendations from the Automated Decision Systems (ADS) Task Force Report required by Local Law 49 of 2018, published here.

“Fairness and equity are central to improving the lives of New Yorkers,” said Mayor Bill de Blasio.“With every new technology comes added responsibility, and I look forward to welcoming an Algorithms Management and Policy Officer to my team to ensure the tools we use to make decisions are fair and transparent.”…

The Algorithms Management and Policy Officer will develop guidelines and best practices to assist City agencies in their use of tools or systems that rely on algorithms and related technologies to support decision-making. As part of that effort, the Officer and their personnel support will develop processes for agency reporting and provide resources that will help the public learn more about how New York City government uses algorithms to make decisions and deliver services….(More)”.

AI For Good Is Often Bad

Curated on Posted on by Stefaan Verhulst

Mark Latonero at Wired: “….Within the last few years, a number of tech companies, from Google to Huawei, have launched their own programs under the AI for Good banner. They deploy technologies like machine-learning algorithms to address critical issues like crime, poverty, hunger, and disease. In May, French president Emmanuel Macron invited about 60 leaders of AI-driven companies, like Facebook’s Mark Zuckerberg, to a Tech for Good Summit in Paris. The same month, the United Nations in Geneva hosted its third annual AI for Global Good Summit sponsored by XPrize. (Disclosure: I have spoken at it twice.) A recent McKinsey report on AI for Social Good provides an analysis of 160 current cases claiming to use AI to address the world’s most pressing and intractable problems.

While AI for good programs often warrant genuine excitement, they should also invite increased scrutiny. Good intentions are not enough when it comes to deploying AI for those in greatest need. In fact, the fanfare around these projects smacks of tech solutionism, which can mask root causes and the risks of experimenting with AI on vulnerable people without appropriate safeguards.

Tech companies that set out to develop a tool for the common good, not only their self-interest, soon face a dilemma: They lack the expertise in the intractable social and humanitarian issues facing much of the world. That’s why companies like Intel have partnered with National Geographic and the Leonardo DiCaprio Foundation on wildlife trafficking. And why Facebook partnered with the Red Cross to find missing people after disasters. IBM’s social-good program alone boasts 19 partnerships with NGOs and government agencies. Partnerships are smart. The last thing society needs is for engineers in enclaves like Silicon Valley to deploy AI tools for global problems they know little about….(More)”.

The Trace

Curated on Posted on by Stefaan Verhulst

About: “The Trace is an independent, nonpartisan, nonprofit newsroom dedicated to shining a light on America’s gun violence crisis….

Every year in our country, a firearm is used in nearly 500,000 crimes, resulting in the deaths and injuries of more than 110,000 people. Shootings devastate families and communities and drain billions of dollars from local, state, and federal governments. Meanwhile, the problem of gun violence has been compounded by another: the shortage of knowledge about the issue…

Data and records are shielded from public view—or don’t exist. Gun-lobby backed restrictions on federal gun violence research deprive policymakers and public health experts of potentially life-saving facts. Other laws limit the information that law enforcement agencies can share on illegal guns and curb litigation that could allow scrutiny of industry practices….

We make the problem clear. In partnership with Slate, we built an eye-opening, interactive map plotting the locations of nearly 40,000 incidents of gun violence nationwide. The feature received millions of pageviews and generated extensive local coverage and social media conversation. “So many shootings and deaths, so close to my home,” wrote one reader. “And I hadn’t even heard about most of them.”…(More)”.

Americans’ views about privacy, surveillance and data-sharing

Curated on Posted on by Stefaan Verhulst

Pew Research Center: “In key ways, today’s digitally networked society runs on quid pro quos: People exchange details about themselves and their activities for services and products on the web or apps. Many are willing to accept the deals they are offered in return for sharing insight about their purchases, behaviors and social lives. At times, their personal information is collected by government on the grounds that there are benefits to public safety and security.

A majority of Americans are concerned about this collection and use of their data, according to a new report from Pew Research Center….

Americans vary in their attitudes toward data-sharing in the pursuit of public good. Though many Americans don’t think they benefit much from the collection of their data, and they find that the potential risks of this practice outweigh the benefits, there are some scenarios in which the public is more likely to accept the idea of data-sharing. In line with findings in a 2015 Center survey showing that some Americans are comfortable with trade-offs in sharing data, about half of U.S. adults (49%) say it is acceptable for the government to collect data about all Americans in order to assess potential terrorist threats. That compares with 31% who feel it is unacceptable to collect data about all Americans for that purpose. By contrast, just one-quarter say it is acceptable for smart speaker makers to share users’ audio recordings with law enforcement to help with criminal investigations, versus 49% who find that unacceptable….(More)”.

Decision-making in the Age of the Algorithm

Curated on Posted on by Stefaan Verhulst

Paper by Thea Snow: “Frontline practitioners in the public sector – from social workers to police to custody officers – make important decisions every day about people’s lives. Operating in the context of a sector grappling with how to manage rising demand, coupled with diminishing resources, frontline practitioners are being asked to make very important decisions quickly and with limited information. To do this, public sector organisations are turning to new technologies to support decision-making, in particular, predictive analytics tools, which use machine learning algorithms to discover patterns in data and make predictions.

While many guides exist around ethical AI design, there is little guidance on how to support a productive human-machine interaction in relation to AI. This report aims to fill this gap by focusing on the issue of human-machine interaction. How people are working with tools is significant because, simply put, for predictive analytics tools to be effective, frontline practitioners need to use them well. It encourages public sector organisations to think about how people feel about predictive analytics tools – what they’re fearful of, what they’re excited about, what they don’t understand.

Based on insights drawn from an extensive literature review, interviews with frontline practitioners, and discussions with experts across a range of fields, the guide also identifies three key principles that play a significant role in supporting a constructive human-machine relationship: context, understanding, and agency….(More)”.

Data as oil, infrastructure or asset? Three metaphors of data as economic value

Curated on Posted on by Stefaan Verhulst

Jan Michael Nolin at the Journal of Information, Communication and Ethics in Society: “Principled discussions on the economic value of data are frequently pursued through metaphors. This study aims to explore three influential metaphors for talking about the economic value of data: data are the new oil, data as infrastructure and data as an asset.

With the help of conceptual metaphor theory, various meanings surrounding the three metaphors are explored. Meanings clarified or hidden through various metaphors are identified. Specific emphasis is placed on the economic value of ownership of data.

In discussions on data as economic resource, the three different metaphors are used for separate purposes. The most used metaphor, data are the new oil, communicates that ownership of data could lead to great wealth. However, with data as infrastructure data have no intrinsic value. Therefore, profits generated from data resources belong to those processing the data, not those owning it. The data as an asset metaphor can be used to convince organizational leadership that they own data of great value….(More)”.

Study says ‘specific’ weather forecasts can’t be made more than 10 days in advance

Curated on Posted on by Stefaan Verhulst

Matthew Cappucci at the Washington Post: “Imagine someone telling you the weather forecast for New Year’s Day today, two months in advance, with exact temperature bounds and rainfall to a hundredth of an inch. Sounds too good to be true, yes?

A new study in Science says it’s simply not possible. But just how far can we take a day-by-day forecast?

The practical limit to daily forecasting

“A skillful forecast lead time of midlatitude instantaneous weather is around 10 days, which serves as the practical predictability limit,” according to a study published in April in the Journal of the Atmospheric Sciences.

Those limits aren’t likely to change much anytime soon. Even if scientists had the data they needed and a more perfect understanding of all forecasting’s complexities, skillful forecasts could extend out to about 14 or 15 days only, the 2019 study found, because of the chaotic nature of the atmosphere.

“Two weeks is about right. It’s as close to be the ultimate limit as we can demonstrate,” the study’s lead author told Science Magazine.

The American Meteorological Society agrees. Their statement on the limits of prediction, in place since 2015, states that “presently, forecasts of daily or specific weather conditions do not exhibit useful skill beyond eight days, meaning that their accuracy is low.”


Although the American Meteorological Society strongly advises against issuing specific forecasts beyond eight days, popular weather vendor AccuWeather has, for years, churned out detailed predictions many days further into the future. It initiated 45-day forecasts in 2013, which it extended to 90 days in 2016 — and has been heavily criticized for it….(More)”.

Big Data, Big Impact? Towards Gender-Sensitive Data Systems

Curated on Posted on by Stefaan Verhulst

Report by Data2X: “How can insights drawn from big data sources improve understanding about the lives of women and girls?

This question has underpinned Data2X’s groundbreaking work at the intersection of big data and gender — work that funded ten research projects that examined the potential of big data to fill the global gender data gap.

Big Data, Big Impact? Towards Gender-Sensitive Data Systems summarizes the findings and potential policy implications of the Big Data for Gender pilot projects funded by Data2X, and lays out five cross-cutting messages that emerge from this body of work:

  1. Big data offers unique insights on women and girls.
  2. Gender-sensitive big data is ready to scale and integrate with traditional data.
  3. Identify and correct bias in big datasets.
  4. Protect the privacy of women and girls.
  5. Women and girls must be central to data governance.

This report argues that the time for pilot projects has passed. Data privacy concerns must be addressed; investment in scale up is needed. Big data offers great potential for women and girls, and indeed for all people….(More)”.

Google’s ‘Project Nightingale’ Gathers Personal Health Data on Millions of Americans

Curated on Posted on by Stefaan Verhulst

Rob Copeland at Wall Street Journal: “Google is engaged with one of the U.S.’s largest health-care systems on a project to collect and crunch the detailed personal-health information of millions of people across 21 states.

The initiative, code-named “Project Nightingale,” appears to be the biggest effort yet by a Silicon Valley giant to gain a toehold in the health-care industry through the handling of patients’ medical data. Amazon.com Inc., Apple Inc.  and Microsoft Corp. are also aggressively pushing into health care, though they haven’t yet struck deals of this scope.

Google began Project Nightingale in secret last year with St. Louis-based Ascension, a Catholic chain of 2,600 hospitals, doctors’ offices and other facilities, with the data sharing accelerating since summer, according to internal documents.

The data involved in the initiative encompasses lab results, doctor diagnoses and hospitalization records, among other categories, and amounts to a complete health history, including patient names and dates of birth….

Neither patients nor doctors have been notified. At least 150 Google employees already have access to much of the data on tens of millions of patients, according to a person familiar with the matter and the documents.

In a news release issued after The Wall Street Journal reported on Project Nightingale on Monday, the companies said the initiative is compliant with federal health law and includes robust protections for patient data….(More)”.

Angela Merkel urges EU to seize control of data from US tech titans

Curated on Posted on by Stefaan Verhulst

Guy Chazan at the Financial Times: “Angela Merkel has urged Europe to seize control of its data from Silicon Valley tech giants, in an intervention that highlights the EU’s growing willingness to challenge the US dominance of the digital economy.

The German chancellor said the EU should claim “digital sovereignty” by developing its own platform to manage data and reduce its reliance on the US-based cloud services run by Amazon, Microsoft and Google. “So many companies have just outsourced all their data to US companies,” Ms Merkel told German business leaders. “I’m not saying that’s bad in and of itself — I just mean that the value-added products that come out of that, with the help of artificial intelligence, will create dependencies that I’m not sure are a good thing.”

Her speech, at an employers’ conference in Berlin, shows the extent to which the information economy is emerging as a battleground in the EU-US trading relationship. It also highlights the concern in European capitals that the EU could be weakened by the market dominance of the big US tech companies, particularly in the business of storing, processing and analysing data.

Margrethe Vestager, the EU’s powerful competition chief who is now also to oversee EU digital policy, last month told the Financial Times that she was examining whether large internet companies could be held to higher standards of proof in competition cases, as part of a tougher line on dominant companies, such as Google.

Ms Merkel was speaking just two weeks after Berlin unveiled plans for a European cloud computing initiative, dubbed Gaia-X, which it has described as a “competitive, safe and trustworthy data infrastructure for Europe”.

At the conference on Tuesday, Peter Altmaier, economy minister, said the data of companies such as Volkswagen, and that of the German interior ministry and social security system, were increasingly stored on the servers of Microsoft and Amazon. “And in this we are losing part of our sovereignty,” he added….(More)”.