privacy

Explaining Explanations in AI

Curated on November 25, 2018November 29, 2018 by Stefaan Verhulst

Paper by Brent Mittelstadt Chris Russell and Sandra Wachter: “Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions. These models are a useful pedagogical device for teaching trained professionals how to predict what decisions will be made by the complex system, and most importantly how the system might break. However, when considering any such model it’s important to remember Box’s maxim that “All models are wrong but some are useful.”

We focus on the distinction between these models and explanations in philosophy and sociology. These models can be understood as a “do it yourself kit” for explanations, allowing a practitioner to directly answer “what if questions” or generate contrastive explanations without external assistance. Although a valuable ability, giving these models as explanations appears more difficult than necessary, and other forms of explanation may not have the same trade-offs. We contrast the different schools of thought on what makes an explanation, and suggest that machine learning might benefit from viewing the problem more broadly… (More)”.

Big Data Ethics and Politics: Toward New Understandings

Curated on November 20, 2018November 20, 2018 by Stefaan Verhulst

Introductory paper by Wenhong Chen and Anabel Quan-Haase of Special Issue of the Social Science Computer Review: “The hype around big data does not seem to abate nor do the scandals. Privacy breaches in the collection, use, and sharing of big data have affected all the major tech players, be it Facebook, Google, Apple, or Uber, and go beyond the corporate world including governments, municipalities, and educational and health institutions. What has come to light is that enabled by the rapid growth of social media and mobile apps, various stakeholders collect and use large amounts of data, disregarding the ethics and politics.

As big data touch on many realms of daily life and have profound impacts in the social world, the scrutiny around big data practice becomes increasingly relevant. This special issue investigates the ethics and politics of big data using a wide range of theoretical and methodological approaches. Together, the articles provide new understandings of the many dimensions of big data ethics and politics, showing it is important to understand and increase awareness of the biases and limitations inherent in big data analysis and practices….(More)”

Startup Offers To Sequence Your Genome Free Of Charge, Then Let You Profit From It

Curated on November 20, 2018November 20, 2018 by Stefaan Verhulst

Richard Harris at NPR: “A startup genetics company says it’s now offering to sequence your entire genome at no cost to you. In fact, you would own the data and may even be able to make money off it.

Nebula Genomics, created by the prominent Harvard geneticist George Church and his lab colleagues, seeks to upend the usual way genomic information is owned.

Today, companies like 23andMe make some of their money by scanning your genetic patterns and then selling that information to drug companies for use in research. (You choose whether to opt in.)

Church says his new enterprise leaves ownership and control of the data in an individual’s hands. And the genomic analysis Nebula will perform is much more detailed than what 23andMe and similar companies offer.

Nebula will do a full genome sequence, rather than a snapshot of key gene variants. That wider range of genetic information would makes the data more appealing to biologists and biotech and pharmaceutical companies….

Church’s approach is part of a trend that’s pushing back against the multibillion-dollar industry to buy and sell medical information. Right now, companies reap those profits and control the data.

“Patients should have the right to decide for themselves whether they want to share their medical data, and, if so, with whom,” Adam Tanner, at Harvard’s Institute for Quantitative Social Science, says in an email. “Efforts to empower people to fine-tune the fate of their medical information are a step in the right direction.” Tanner, author of a book on the subject of the trade in medical data, isn’t involved in Nebula.

The current system is “very paternalistic,” Church says. He aims to give people complete control over who gets access to their data, and let individuals decide whether or not to sell the information, and to whom.

“In this case, everything is private information, stored on your computer or a computer you designate,” Church says. It can be encrypted so nobody can read it, even you, if that’s what you want.

Drug companies interested in studying, say, diabetes patients would ask Nebula to identify people in their system who have the disease. Nebula would then identify those individuals by launching an encrypted search of participants.

People who have indicated they’re interested in selling their genetic data to a company would then be given the option of granting access to the information, along with medical data that person has designated.

Other companies are also springing up to help people control — and potentially profit from — their medical data. EncrypGen lets people offer up their genetic data, though customers have to provide their own DNA sequence. Hu-manity.co is also trying to establish a system in which people can sell their medical data to pharmaceutical companies….(More)”.

What do we learn from Machine Learning?

Curated on November 19, 2018May 29, 2019 by Stefaan Verhulst

Blog by Giovanni Buttarelli: “…There are few authorities monitoring the impact of new technologies on fundamental rights so closely and intensively as data protection and privacy commissioners. At the International Conference of Data Protection and Privacy Commissioners, the 40th ICDPPC (which the EDPS had the honour to host), they continued the discussion on AI which began in Marrakesh two years ago with a reflection paper prepared by EDPS experts. In the meantime, many national data protection authorities have invested considerable efforts and provided important contributions to the discussion. To name only a few, the data protection authorities from Norway, France, the UK and Schleswig-Holstein have published research and reflections on AI, ethics and fundamental rights. We all see that some applications of AI raise immediate concerns about data protection and privacy; but it also seems generally accepted that there are far wider-reaching ethical implications, as a group of AI researchers also recently concluded. Data protection and privacy commissioners have now made a forceful intervention by adopting a declaration on ethics and data protection in artificial intelligence which spells out six principles for the future development and use of AI – fairness, accountability, transparency, privacy by design, empowerment and non-discrimination – and demands concerted international efforts to implement such governance principles. Conference members will contribute to these efforts, including through a new permanent working group on Ethics and Data Protection in Artificial Intelligence.

The ICDPPC was also chosen by an alliance of NGOs and individuals, The Public Voice, as the moment to launch its own Universal Guidelines on Artificial Intelligence (UGAI). The twelve principles laid down in these guidelines extend and complement those of the ICDPPC declaration.

We are only at the beginning of this debate. More voices will be heard: think tanks such as CIPL are coming forward with their suggestions, and so will many other organisations.

At international level, the Council of Europe has invested efforts in assessing the impact of AI, and has announced a report and guidelines to be published soon. The European Commission has appointed an expert group which will, among other tasks, give recommendations on future-related policy development and on ethical, legal and societal issues related to AI, including socio-economic challenges.

As I already pointed out in an earlier blogpost, it is our responsibility to ensure that the technologies which will determine the way we and future generations communicate, work and live together, are developed in such a way that the respect for fundamental rights and the rule of law are supported and not undermined….(More)”.

Sidewalk Labs: Privacy in a City Built from the Internet Up

Curated on November 17, 2018November 17, 2018 by Stefaan Verhulst

Harvard Business School Case Study by Leslie K. John, Mitchell Weiss and Julia Kelley: “By the time Dan Doctoroff, CEO of Sidewalk Labs, began hosting a Reddit “Ask Me Anything” session in January 2018, he had only nine months remaining to convince the people of Toronto, their government representatives, and presumably his parent company Alphabet, Inc., that Sidewalk Labs’ plan to construct “the first truly 21st-century city” on the Canadian city’s waterfront was a sound one. Along with much excitement and optimism, strains of concern had emerged since Doctoroff and partners first announced their intentions for a city “built from the internet up” in Toronto’s Quayside district. As Doctoroff prepared for yet another milestone in a year of planning and community engagement, it was almost certain that of the many questions headed his way, digital privacy would be among them….(More)”.

Artificial Intelligence: Risks to Privacy and Democracy

Curated on November 15, 2018November 15, 2018 by Stefaan Verhulst

Karl Manheim and Lyric Kaplan at Yale Journal of Law and Technology: “A “Democracy Index” is published annually by the Economist. For 2017, it reported that half of the world’s countries scored lower than the previous year. This included the United States, which was demoted from “full democracy” to “flawed democracy.” The principal factor was “erosion of confidence in government and public institutions.” Interference by Russia and voter manipulation by Cambridge Analytica in the 2016 presidential election played a large part in that public disaffection.

Threats of these kinds will continue, fueled by growing deployment of artificial intelligence (AI) tools to manipulate the preconditions and levers of democracy. Equally destructive is AI’s threat to decisional andinforma-tional privacy. AI is the engine behind Big Data Analytics and the Internet of Things. While conferring some consumer benefit, their principal function at present is to capture personal information, create detailed behavioral profiles and sell us goods and agendas. Privacy, anonymity and autonomy are the main casualties of AI’s ability to manipulate choices in economic and political decisions.

The way forward requires greater attention to these risks at the nation-al level, and attendant regulation. In its absence, technology giants, all of whom are heavily investing in and profiting from AI, will dominate not only the public discourse, but also the future of our core values and democratic institutions….(More)”.

Declaration of Cities Coalition for Digital Rights

Curated on November 13, 2018November 14, 2018 by Stefaan Verhulst

New York City, Barcelona and Amsterdam: “We, the undersigned cities, formally come together to form the Cities Coalition for Digital Rights, to protect and uphold human rights on the internet at the local and global level.

The internet has become inseparable from our daily lives. Yet, every day, there are new cases of digital rights abuse, misuse and misinformation and concentration of power around the world: freedom of expression being censored; personal information, including our movements and communications, monitored, being shared and sold without consent; ‘black box’ algorithms being used to make unaccountable decisions; social media being used as a tool of harassment and hate speech; and democratic processes and public opinion being undermined.

As cities, the closest democratic institutions to the people, we are committed to eliminating impediments to harnessing technological opportunities that improve the lives of our constituents, and to providing trustworthy and secure digital services and infrastructures that support our communities. We strongly believe that human rights principles such as privacy, freedom of expression, and democracy must be incorporated by design into digital platforms starting with locally-controlled digital infrastructures and services.

As a coalition, and with the support of the United Nations Human Settlements Program (UN-Habitat), we will share best practices, learn from each other’s challenges and successes, and coordinate common initiatives and actions. Inspired by the Internet Rights and Principles Coalition (IRPC), the work of 300 international stakeholders over the past ten years, we are committed to the following five evolving principles:

01.Universal and equal access to the internet, and digital literacy

02.Privacy, data protection and security

03.Transparency, accountability, and non-discrimination of data, content and algorithms

04.Participatory Democracy, diversity and inclusion

05.Open and ethical digital service standards”

NHS Pulls Out Of Data-Sharing Deal With Home Office Immigration Enforcers

Curated on November 13, 2018November 15, 2018 by Stefaan Verhulst

Jasmin Gray at Huffington Post: “The NHS has pulled out of a controversial data-sharing arrangement with the Home Office which saw confidential patients’ details passed on to immigration enforcers.

In May, the government suspended the ‘memorandum of understanding’ agreement between the health service and the Home Office after MPs, doctors and health charities warned it was leaving seriously ill migrants too afraid to seek medical treatment.

But on Tuesday, NHS Digital announced that it was cutting itself out of the agreement altogether.

“NHS Digital has received a revised narrowed request from the Home Office and is discussing this request with them,” a spokesperson for the data-branch of the health service said, adding that they have “formally closed-out our participation” in the previous memorandum of understanding.

The anxieties of “multiple stakeholder communities” to ensure the agreement made by the government was respected was taken into account in the decision, they added.

Meanwhile, the Home Office confirmed it was working to agree a new deal with NHS Digital which would only allow it to make requests for data about migrants “facing deportation action because they have committed serious crimes, or where information necessary to protect someone’s welfare”.

The move has been welcomed by campaigners, with Migrants’ Rights Network director Rita Chadra saying that many migrants had missed out on “the right to privacy and access to healthcare” because of the data-sharing mechanism….(More)”.

Beyond Open vs. Closed: Balancing Individual Privacy and Public Accountability in Data Sharing

Curated on November 7, 2018November 15, 2018 by Stefaan Verhulst

Paper by Bill Howe et al: “Data too sensitive to be “open” for analysis and re-purposing typically remains “closed” as proprietary information. This dichotomy undermines efforts to make algorithmic systems more fair, transparent, and accountable. Access to proprietary data in particular is needed by government agencies to enforce policy, researchers to evaluate methods, and the public to hold agencies accountable; all of these needs must be met while preserving individual privacy and firm competitiveness. In this paper, we describe an integrated legaltechnical approach provided by a third-party public-private data trust designed to balance these competing interests.

Basic membership allows firms and agencies to enable low-risk access to data for compliance reporting and core methods research, while modular data sharing agreements support a wide array of projects and use cases. Unless specifically stated otherwise in an agreement, all data access is initially provided to end users through customized synthetic datasets that offer a) strong privacy guarantees, b) removal of signals that could expose competitive advantage for the data providers, and c) removal of biases that could reinforce discriminatory policies, all while maintaining empirically good fidelity to the original data. We find that the liberal use of synthetic data, in conjunction with strong legal protections over raw data, strikes a tunable balance between transparency, proprietorship, privacy, and research objectives; and that the legal-technical framework we describe can form the basis for organizational data trusts in a variety of contexts….(More)”.