Crowdsourced Morality Could Determine the Ethics of Artificial Intelligence


Dom Galeon in Futurism: “As artificial intelligence (AI) development progresses, experts have begun considering how best to give an AI system an ethical or moral backbone. A popular idea is to teach AI to behave ethically by learning from decisions made by the average person.

To test this assumption, researchers from MIT created the Moral Machine. Visitors to the website were asked to make choices regarding what an autonomous vehicle should do when faced with rather gruesome scenarios. For example, if a driverless car was being forced toward pedestrians, should it run over three adults to spare two children? Save a pregnant woman at the expense of an elderly man?

The Moral Machine was able to collect a huge swath of this data from random people, so Ariel Procaccia from Carnegie Mellon University’s computer science department decided to put that data to work.

In a new study published online, he and Iyad Rahwan — one of the researchers behind the Moral Machine — taught an AI using the Moral Machine’s dataset. Then, they asked the system to predict how humans would want a self-driving car to react in similar but previously untested scenarios….

This idea of having to choose between two morally problematic outcomes isn’t new. Ethicists even have a name for it: the double-effect. However, having to apply the concept to an artificially intelligent system is something humankind has never had to do before, and numerous experts have shared their opinions on how best to go about it.

OpenAI co-chairman Elon Musk believes that creating an ethical AI is a matter of coming up with clear guidelines or policies to govern development, and governments and institutions are slowly heeding Musk’s call. Germany, for example, crafted the world’s first ethical guidelines for self-driving cars. Meanwhile, Google parent company Alphabet’s AI DeepMind now has an ethics and society unit.

Other experts, including a team of researchers from Duke University, think that the best way to move forward is to create a “general framework” that describes how AI will make ethical decisions….(More)”.

Using Facebook data as a real-time census


Phys.org: “Determining how many people live in Seattle, perhaps of a certain age, perhaps from a specific country, is the sort of question that finds its answer in the census, a massive data dump for places across the country.

But just how fresh is that data? After all, the census is updated once a decade, and the U.S. Census Bureau’s smaller but more detailed American Community Survey, annually. There’s also a delay between when data are collected and when they are published. (The release of data for 2016 started gradually in September 2017.)

Enter Facebook, which, with some caveats, can serve as an even more current source of , especially about migrants. That’s the conclusion of a study led by Emilio Zagheni, associate professor of sociology at the University of Washington, published Oct. 11 in Population and Development Review. The study is believed to be the first to demonstrate how present-day migration statistics can be obtained by compiling the same data that advertisers use to target their audience on Facebook, and by combining that source with information from the Census Bureau.

Migration indicates a variety of political and economic trends and is a major driver of population change, Zagheni said. As researchers further explore the increasing number of databases produced for advertisers, Zagheni argues, social scientists could leverage Facebook, LinkedIn and Twitter more often to glean information on geography, mobility, behavior and employment. And while there are some limits to the data – each platform is a self-selected, self-reporting segment of the population – the number of migrants according to Facebook could supplement the official numbers logged by the U.S. Census Bureau, Zagheni said….(Full Paper).

When Cartography Meets Disaster Relief


Mimi Kirk at CityLab: “Almost three weeks after Hurricane Maria hit Puerto Rico, the island is in a grim state. Fewer than 15 percent of residents have power, and much of the island has no clean drinking water. Delivery of food and other necessities, especially to remote areas, has been hampered by a variety of ills, including a lack of cellular service, washed-out roads, additional rainfall, and what analysts and Puerto Ricans say is a slow and insufficient response from the U.S. government.

Another issue slowing recovery? Maps—or lack of them. While pre-Maria maps of Puerto Rico were fairly complete, their level of detail was nowhere near that of other parts of the United States. Platforms such as Google Maps are more comprehensive on the mainland than on the island, explains Juan Saldarriaga, a research scholar at the Center for Spatial Research at Columbia University. This is because companies like Google often create maps for financial reasons, selling them to advertisers or as navigation devices, so areas that have less economic activity are given less attention.

This lack of detail impedes recovery efforts: Without basic information on the location of buildings, for instance, rescue workers don’t know how many people were living in an area before the hurricane struck—and thus how much aid is needed.

Crowdsourced mapping can help. Saldarriaga recently organized a “mapathon” at Columbia, in which volunteers examined satellite imagery of Puerto Rico and added missing buildings, roads, bridges, and other landmarks in the open-source platform OpenStreetMap. While some universities and other groups are hosting similar events, anyone with an internet connection and computer can participate.

Saldarriaga and his co-organizers collaborated with Humanitarian OpenStreetMap Team (HOT), a nonprofit that works to create crowdsourced maps for aid and development work. Volunteers like Saldarriaga largely drive HOT’s “crisis mapping” projects, the first of which occurred in 2010 after Haiti’s earthquake…(More)”.

Open mapping from the ground up: learning from Map Kibera


Report by Erica Hagen for Making All Voices Count: “In Nairobi in 2009, 13 young residents of the informal settlement of Kibera mapped their community using OpenStreetMap, an online mapping platform. This was the start of Map Kibera, and eight years of ongoing work to date on digital mapping, citizen media and open data. In this paper, Erica Hagen – one of the initiators of Map Kibera – reflects on the trajectory of this work. Through research interviews with Map Kibera staff, participants and clients, and users of the data and maps the project has produced, she digs into what it means for citizens to map their communities, and examines the impact of open local information on members of the community. The paper begins by situating the research and Map Kibera in selected literature on transparency, accountability and mapping. It then presents three case studies of mapping in Kibera – in the education, security and water sectors – discussing evidence about the effects not only on project participants, but also on governmental and non-governmental actors in each of the three sectors. It concludes that open, community-based data collection can lead to greater trust, which is sorely lacking in marginalised places. In large-scale data gathering, it is often unclear to those involved why the data is needed or what will be done with it. But the experience of Map Kibera shows that by starting from the ground up and sharing open data widely, it is possible to achieve strong sector-wide ramifications beyond the scope of the initial project, including increased resources and targeting by government and NGOs. While debates continue over the best way to truly engage citizens in the ‘data revolution’ and tracking the Sustainable Development Goals, the research here shows that engaging people fully in the information value chain can be the missing link between data as a measurement tool, and information having an impact on social development….(More)”.

what3words


what3words: “Street addresses worldwide are inaccurate, unreliable and don’t exist at all in many places. Poor addressing is expensive and frustrating, hampers economic growth and development, restricts social mobility and affects lives.

Inaccurate addressing limits businesses and frustrates customers

Street addresses can usually identify a building, but aren’t accurate enough to help a courier or taxi driver find the correct entrance. This results in delayed or failed deliveries, and numerous ‘where are you’ phone calls.

There’s no human-friendly way to give a location to a machine

As personal devices, autonomous vehicles and the IoT streamline the way we live, we have an increasing need to communicate very accurate location. Addresses are too broad to direct a drone or an autonomous car, whilst GPS coordinates are complicated and prone to input mistakes.

Billions of people worldwide have no reliable address at all

Without an address, people struggle to access health and education services, register land and vote. Many of these people live in rapidly expanding cities, or informal settlements….

what3words is the simplest way to talk about any precise location. Our system has divided the world into a grid of 3m x 3m squares and assigned each one a unique address made of just 3 words. Now everyone and everywhere has a reliable address….(More)”.

The Digital Social Innovation Manifesto


ChiC: “The unprecedented hyper connectivity enabled by digital technologies and the Internet are rapidly changing the opportunities we have to address some of the society’s biggest challenges: environmental preservation, reducing inequalities, fostering inclusion and putting in place sustainable economic models.
However, to make the most of these opportunities we need to move away from the current centralization of power by a small number of large tech companies and enable a much broader group of people and organisations to develop and share innovative digital solutions.

Across Europe, a growing movement of people is exploring opportunities for Digital Social Innovation (DSI), developing bottom-up solutions leveraging on participation, collaboration, decentralization, openness, and multi-disciplinarity. However, it is still at a relatively small scale, because of the little public and private investment in DSI, the limited experience in large-scale take-up of collective solutions, and the relative lack of skills of DSI actors (civil society) compared to commercial companies.

This Manifesto aims at fostering civic participation into democratic and social processes, increasing societal resilience and mutual trust as core element of the Digital Society. It provides recommendations for policy makers, to drive the development of the European Digital Single Market to fulfill first and foremost societal and sustainability challenges (rather than short-lived economic interests), with the help and engagement of all citizens.

This Manifesto reflects the views of a broad community of innovators, catalyzed by the coordination action ChiC, which is funded by the European Commission, within the context of the CAPS initiative. As such, it is open to incorporating incoming views and opinions from other stakeholders and it does not intend to promote the specific commercial interests of actors of any kind….(More)”

UN Opens New Office to Monitor AI Development and Predict Possible Threats


Interesting Engineering: “The United Nations has created a new office in the Netherlands dedicated to the monitoring and research of Artificial Intelligence (AI) technologies. The new office will collect information about the way in which AI is impacting the world. Researchers will have a particular focus on the way AI relates to global security but will also monitor the effects of job loss from AI and automation.

Irakli Beridze, a UN senior strategic adviser will head the office. They have described the new office saying, “A number of UN organisations operate projects involving robots and AI, such as the group of experts studying the role of autonomous military robots in the realm of conventional weapons. These are temporary measures. Ours is the first permanent UN office on this subject. We are looking at the risks as well as the advantages.”….He suggests that the speed of AI technology development is of primary concern. He explains, “This can make for instability if society does not adapt quickly enough. One of our most important tasks is to set up a network of experts from business, knowledge institutes, civil society organisations and governments. We certainly do not want to plead for a ban or a brake on technologies. We will also explore how new technology can contribute to the sustainable development goals of the UN. For this, we want to start concrete projects. We will not be a talking club.”…(More).

Co-creating an Open Government Data Driven Public Service: The Case of Chicago’s Food Inspection Forecasting Model


Conference paper by Keegan Mcbride et al: “Large amounts of Open Government Data (OGD) have become available and co-created public services have started to emerge, but there is only limited empirical material available on co-created OGD-driven public services. The authors have built a conceptual model around an innovation process based on the ideas of co-production and agile development for co-created OGD-driven public service. An exploratory case study on Chicago’s use of OGD in a predictive analytics model that forecasts critical safety violations at food serving establishments was carried out to expose the intricate process of how co-creation occurs and what factors allow for it to take place. Six factors were identified as playing a key role in allowing the co-creation of an OGD-driven public service to take place: external funding, motivated stakeholders, innovative leaders, proper communication channels, an existing OGD portal, and agile development practices. The conceptual model was generally validated, but further propositions on co-created OGD-driven public services emerged. These propositions state that the availability of OGD and tools for data analytics have the potential to enable the co-creation of OGD-driven public services, governments releasing OGD are acting as a platform and from this platform the co-creation of new and innovative OGD-driven public services may take place, and that the idea of Government as a Platform (GaaP) does appear to be an idea that allows for the topics of co-creation and OGD to be merged together….(More)”.

Ethical Guidelines for Applying Predictive Tools Within Human Services


MetroLab Network: “Predictive analytical tools are already being put to work within human service agencies to help make vital decisions about when and how to intervene in the lives of families and communities. The sector may not be entirely comfortable with this trend, but it should not be surprised. Predictive models are in wide use within the justice and education sectors and, more to the point, they work: risk assessment is fundamental to what social services do, and these tools can help agencies respond more quickly to prevent harm, to create more personalized interventions, and allocate scarce public resources to where they can do the most good.

There is also a strong case that predictive risk models (PRM) can reduce bias in decision-making. Designing a predictive model forces more explicit conversations about how agencies think about different risk factors and how they propose to guard against disadvantaging certain demographic or socioeconomic groups. And the standard that agencies are trying to improve upon is not perfect equity—it is the status quo, which is neither transparent nor uniformly fair. Risk scores do not eliminate the possibility of personal or institutional prejudice but they can make it more apparent by providing a common reference point.

That the use of predictive analytics in social services can reduce bias is not to say that it will. Careless or unskilled development of these predictive tools could worsen disparities among clients receiving social services. Child and civil rights advocates rightly worry about the potential for “net widening”—drawing more people in for unnecessary scrutiny by the government. They worry that rather than improving services for vulnerable clients, these models will replicate the biases in existing public data sources and expose them to greater trauma. Bad models scale just as quickly as good ones, and even the best of them can be misused.

The stakes here are real: for children and families that interact with these social systems and for the reputation of the agencies that turn to these tools. What, then, should a public leader know about risk modeling, and what lessons does it offer about how to think about data science, data stewardship, and the public interest?…(More)”.

Gamification, Participatory Democracy and Engaged Public(s)


Paper by Gianluca Sgueo: “The use of game-design elements – a phenomenon known as ‘gamification’ – features prominently within on-going processes of innovation of governance. According to the research and advisory firm Gartner, 2,000 of the top public organizations worldwide have at least one gamified application and/or process in place. Examples of gamification in public governance include “Run that town” (ideated by the Australian Bureau of Statistics to raise citizens’ awareness of the national census), the “Red Balloon Challenge” (initiated by the United States’ Defence Advanced Research Project Agency to test systems for improving cooperation among soldiers, experts and diplomatic officers overseas), and “Manor Labs” (a web platform that awarded “Innobucks”, a type of virtual commodity, to residents of the City of Manor, in Texas, for proposing ideas related with urban development).
The purpose of this paper is threefold: first, to determine who is actually participating in public policy processes via gamification; second, to weigh the impact that the public(s) engaged by gamification has on democratic governance; third, to assess the societal environment within which gamification might flourish or establish plausibly….(More)”.