Malicious Uses and Abuses of Artificial Intelligence

Curated on Posted on by Stefaan Verhulst

Report by Europol, the United Nations Interregional Crime and Justice Research Institute (UNICRI) and Trend Micro: “… looking into current and predicted criminal uses of artificial intelligence (AI)… The report provides law enforcers, policy makers and other organizations with information on existing and potential attacks leveraging AI and recommendations on how to mitigate these risks.

“AI promises the world greater efficiency, automation and autonomy. At a time where the public is getting increasingly concerned about the possible misuse of AI, we have to be transparent about the threats, but also look into the potential benefits from AI technology.” said Edvardas Šileris, Head of Europol’s Cybercrime Centre. “This report will help us not only to anticipate possible malicious uses and abuses of AI, but also to prevent and mitigate those threats proactively. This is how we can unlock the potential AI holds and benefit from the positive use of AI systems.”

The report concludes that cybercriminals will leverage AI both as an attack vector and an attack surface. Deepfakes are currently the best-known use of AI as an attack vector. However, the report warns that new screening technology will be needed in the future to mitigate the risk of disinformation campaigns and extortion, as well as threats that target AI data sets.

For example, AI could be used to support:

  • Convincing social engineering attacks at scale
  • Document-scraping malware to make attacks more efficient
  • Evasion of image recognition and voice biometrics
  • Ransomware attacks, through intelligent targeting and evasion
  • Data pollution, by identifying blind spots in detection rules..

The three organizations make several recommendations to conclude the report:

The Next Generation Humanitarian Distributed Platform

Curated on Posted on by Stefaan Verhulst

Report by Mercy Corps, the Danish Red Cross and hiveonline: “… call for the development of a shared, sector-wide “blockchain for good” to allow the aid sector to better automate and track processes in real-time, and maintain secure records. This would help modernize and coordinate the sector to reach more people as increasing threats such as pandemics, climate change and natural disasters require aid to be disbursed faster, more widely and efficiently.

A cross-sector blockchain platform – a digital database that can be simultaneously used and shared within a large decentralized, publicly accessible network – could support applications ranging from cash and voucher distribution to identity services, natural capital and carbon tracking, and donor engagement.

The report authors call for the creation of a committee to develop cross-sector governance and coordinate the implementation of a shared “Humanitarian Distributed Platform.” The authors believe the technology can help organizations fulfill commitments made to transparency, collaboration and efficiency under the Humanitarian Grand Bargain.

The report is compiled from responses of 35 survey participants, representing stakeholders in the humanitarian sector, including NGO project implementers, consultants, blockchain developers, academics, and founders. A further 39 direct interviews took place over the course of the research between July and September 2020….(More)”.

Interoperability as a tool for competition regulation

Curated on Posted on by Stefaan Verhulst

Paper by Ian Brown: “Interoperability is a technical mechanism for computing systems to work together – even if they are from competing firms. An interoperability requirement for large online platforms has been suggested by the European Commission as one ex ante (up-front rule) mechanism in its proposed Digital Markets Act (DMA), as a way to encourage competition. The policy goal is to increase choice and quality for users, and the ability of competitors to succeed with better services. The application would be to the largest online platforms, such as Facebook, Google, Amazon, smartphone operating systems (e.g. Android/iOS), and their ancillary services, such as payment and app stores.

This report analyses up-front interoperability requirements as a pro-competition policy tool for regulating large online platforms, exploring the economic and social rationales and possible regulatory mechanisms. It is based on a synthesis of recent comprehensive policy re-views of digital competition in major industrialised economies, and related academic literature, focusing on areas of emerging consensus while noting important disagreements. It draws particularly on the Vestager, Furman and Stigler reviews, and the UK Competition and Markets Authority’s study on online platforms and digital advertising. It also draws on interviews with software developers, platform operators, government officials, and civil society experts working in this field….(More)”.

Curating citizen engagement: Food solutions for future generations

Curated on Posted on by Stefaan Verhulst

EIT Food: “The Curating Citizen Engagement project will revolutionise our way of solving grand societal challenges by creating a platform for massive public involvement and knowledge generation, specifically targeting food-related issues. …Through a university course developed by partners representing different aspects of the food ecosystem (from sensory perception to nutrition to food policy), we will educate the next generation of students to be able to engage and involve the public in tackling food-related societal challenges. The students will learn iterative prototyping skills in order to create museum installations with built-in data collection points, that will engage the public and assist in shaping future food solutions. Thus, citizens are not only provided with knowledge on food related topics, but are empowered and encouraged to actively use it, leading to more trust in the food sector in general….(More)”.

Using artificial intelligence to make decisions: Addressing the problem of algorithmic bias (2020)

Curated on Posted on by Stefaan Verhulst

Foreword of a Report by the Australian Human Rights Commission: “Artificial intelligence (AI) promises better, smarter decision making.

Governments are starting to use AI to make decisions in welfare, policing and law enforcement, immigration, and many other areas. Meanwhile, the private sector is already using AI to make decisions about pricing and risk, to determine what sorts of people make the ‘best’ customers… In fact, the use cases for AI are limited only by our imagination.

However, using AI carries with it the risk of algorithmic bias. Unless we fully understand and address this risk, the promise of AI will be hollow.

Algorithmic bias is a kind of error associated with the use of AI in decision making, and often results in unfairness. Algorithmic bias can arise in many ways. Sometimes the problem is with the design of the AI-powered decision-making tool itself. Sometimes the problem lies with the data set that was used to train the AI tool, which could replicate or even make worse existing problems, including societal inequality.

Algorithmic bias can cause real harm. It can lead to a person being unfairly treated, or even suffering unlawful discrimination, on the basis of characteristics such as their race, age, sex or disability.

This project started by simulating a typical decision-making process. In this technical paper, we explore how algorithmic bias can ‘creep in’ to AI systems and, most importantly, how this problem can be addressed.

To ground our discussion, we chose a hypothetical scenario: an electricity retailer uses an AI-powered tool to decide how to offer its products to customers, and on what terms. The general principles and solutions for mitigating the problem, however, will be relevant far beyond this specific situation.

Because algorithmic bias can result in unlawful activity, there is a legal imperative to address this risk. However, good businesses go further than the bare minimum legal requirements, to ensure they always act ethically and do not jeopardise their good name.

Rigorous design, testing and monitoring can avoid algorithmic bias. This technical paper offers some guidance for companies to ensure that when they use AI, their decisions are fair, accurate and comply with human rights….(More)”

Responsible Data Re-Use for COVID19

Curated on Posted on by Stefaan Verhulst

” The Governance Lab (The GovLab) at the NYU Tandon School of Engineering, with support from the Henry Luce Foundation, today released guidance to inform decision-making in the responsible re-use of data — re-purposing data for a use other than that for which it was originally intended — to address COVID-19. The findings, recommendations, and a new Responsible Data Re-Use framework stem from The Data Assembly initiative in New York City. An effort to solicit diverse, actionable public input on data re-use for crisis response in the United States, the Data Assembly brought together New York City-based stakeholders from government, the private sector, civic rights and advocacy organizations, and the general public to deliberate on innovative, though potentially risky, uses of data to inform crisis response in New York City. The findings and guidance from the initiative will inform policymaking and practice regarding data re-use in New York City, as well as free data literacy training offerings.

The Data Assembly’s Responsible Data Re-Use Framework provides clarity on a major element of the ongoing crisis. Though leaders throughout the world have relied on data to reduce uncertainty and make better decisions, expectations around the use and sharing of siloed data assets has remained unclear. This summer, along with the New York Public Library and Brooklyn Public Library, The GovLab co-hosted four months of remote deliberations with New York-based civil rights organizations, key data holders, and policymakers. Today’s release is a product of these discussions, to show how New Yorkers and their leaders think about the opportunities and risks involved in the data-driven response to COVID-19….(More)”

See: The Data Assembly Synthesis Report by y Andrew Young, Stefaan G. Verhulst, Nadiya Safonova, and Andrew J. Zahuranec

Don’t Fear the Robots, and Other Lessons From a Study of the Digital Economy

Curated on Posted on by Stefaan Verhulst

Steve Lohr at the New York Times: “L. Rafael Reif, the president of Massachusetts Institute of Technology, delivered an intellectual call to arms to the university’s faculty in November 2017: Help generate insights into how advancing technology has changed and will change the work force, and what policies would create opportunity for more Americans in the digital economy.

That issue, he wrote, is the “defining challenge of our time.”

Three years later, the task force assembled to address it is publishing its wide-ranging conclusions. The 92-page report, “The Work of the Future: Building Better Jobs in an Age of Intelligent Machines,” was released on Tuesday….

Here are four of the key findings in the report:

Most American workers have fared poorly.

It’s well known that those on the top rungs of the job ladder have prospered for decades while wages for average American workers have stagnated. But the M.I.T. analysis goes further. It found, for example, that real wages for men without four-year college degrees have declined 10 to 20 percent since their peak in 1980….

Robots and A.I. are not about to deliver a jobless future.

…The M.I.T. researchers concluded that the change would be more evolutionary than revolutionary. In fact, they wrote, “we anticipate that in the next two decades, industrialized countries will have more job openings than workers to fill them.”…

Worker training in America needs to match the market.

“The key ingredient for success is public-private partnerships,” said Annette Parker, president of South Central College, a community college in Minnesota, and a member of the advisory board to the M.I.T. project.

The schools, nonprofits and corporate-sponsored programs that have succeeded in lifting people into middle-class jobs all echo her point: the need to link skills training to business demand….

Workers need more power, voice and representation.The report calls for raising the minimum wage, broadening unemployment insurance and modifying labor laws to enable collective bargaining in occupations like domestic and home-care workers and freelance workers. Such representation, the report notes, could come from traditional unions or worker advocacy groups like the National Domestic Workers Alliance, Jobs With Justice and the Freelancers Union….(More)”

Leveraging Open Data with a National Open Computing Strategy

Curated on Posted on by Stefaan Verhulst

Policy Brief by Lara Mangravite and John Wilbanks: “Open data mandates and investments in public data resources, such as the Human Genome Project or the U.S. National Oceanic and Atmospheric Administration Data Discovery Portal, have provided essential data sets at a scale not possible without government support. By responsibly sharing data for wide reuse, federal policy can spur innovation inside the academy and in citizen science communities. These approaches are enabled by private-sector advances in cloud computing services and the government has benefited from innovation in this domain. However, the use of commercial products to manage the storage of and access to public data resources poses several challenges.

First, too many cloud computing systems fail to properly secure data against breaches, improperly share copies of data with other vendors, or use data to add to their own secretive and proprietary models. As a result, the public does not trust technology companies to responsibly manage public data—particularly private data of individual citizens. These fears are exacerbated by the market power of the major cloud computing providers, which may limit the ability of individuals or institutions to negotiate appropriate terms. This impacts the willingness of U.S. citizens to have their personal information included within these databases.

Second, open data solutions are springing up across multiple sectors without coordination. The federal government is funding a series of independent programs that are working to solve the same problem, leading to a costly duplication of effort across programs.

Third and most importantly, the high costs of data storage, transfer, and analysis preclude many academics, scientists, and researchers from taking advantage of governmental open data resources. Cloud computing has radically lowered the costs of high-performance computing, but it is still not free. The cost of building the wrong model at the wrong time can quickly run into tens of thousands of dollars.

Scarce resources mean that many academic data scientists are unable or unwilling to spend their limited funds to reuse data in exploratory analyses outside their narrow projects. And citizen scientists must use personal funds, which are especially scarce in communities traditionally underrepresented in research. The vast majority of public data made available through existing open science policy is therefore left unused, either as reference material or as “foreground” for new hypotheses and discoveries….The Solution: Public Cloud Computing…(More)”.

Federal Regulators Increase Focus on Patient Risks From Electronic Health Records

Curated on Posted on by Stefaan Verhulst

Ben Moscovitch at Pew: “…The Office of the National Coordinator for Health Information Technology (ONC) will collect clinicians’ feedback through a survey developed by the Urban Institute under a contract with the agency. ONC will release aggregated results as part its EHR reporting program. Congress required the program’s creation in the 21st Century Cures Act, the wide-ranging federal health legislation enacted in 2016. The act directs ONC to determine which data to gather from health information technology vendors. That information can then be used to illuminate the strengths and weaknesses of EHR products, as well as industry trends.

The Pew Charitable Trusts, major medical organizations and hospital groups, and health information technology experts have urged that the reporting program examine usability-related patient risks. Confusing, cumbersome, and poorly customized EHR systems can cause health care providers to order the wrong drug or miss test results and other information critical to safe, effective treatment. Usability challenges also can increase providers’ frustration and, in turn, their likelihood of making mistakes.

The data collected from clinicians will shed light on these problems, encourage developers to improve the safety of their products, and help hospitals and doctor’s offices make better-informed decisions about the purchase, implementation, and use of these tools. Research shows that aggregated data about EHRs can generate product-specific insights about safety deficiencies, even when health care facilities implement the same system in distinct ways….(More)”.

The Work of the Future: Shaping Technology and Institutions

Curated on Posted on by Stefaan Verhulst

Report by David Autor, David Mindell and Elisabeth Reynolds for the MIT Future of Work Task Force: “The world now stands on the cusp of a technological revolution in artificial intelligence and robotics that may prove as transformative for economic growth and human potential as were electrification, mass production, and electronic telecommunications in their eras. New and emerging technologies will raise aggregate economic output and boost the wealth of nations. Will these developments enable people to attain higher living standards, better working conditions, greater economic security, and improved health and longevity? The answers to these questions are not predetermined. They depend upon the institutions, investments, and policies that we deploy to harness the opportunities and confront the challenges posed by this new era.

How can we move beyond unhelpful prognostications about the supposed end of work and toward insights that will enable policymakers, businesses, and people to better navigate the disruptions that are coming and underway? What lessons should we take from previous epochs of rapid technological change? How is it different this time? And how can we strengthen institutions, make investments, and forge policies to ensure that the labor market of the 21st century enables workers to contribute and succeed?

To help answer these questions, and to provide a framework for the Task Force’s efforts over the next year, this report examines several aspects of the interaction between work and technology….(More)”.