Collection

Artificial intelligence in non-profit organizations

Curated on June 6, 2018May 29, 2019 by Stefaan Verhulst

Darrell M. West and Theron Kelso at Brookings: “Artificial intelligence provides a way to use automated software to perform a number of different tasks. Private industry, government, and universities have deployed it to manage routine requests and common administrative processes. Fields from finance and healthcare to retail and defense are witnessing a dramatic expansion in the use of these tools.

Yet non-profits often lack the financial resources or organizational capabilities to innovate through technology. Most non-profits struggle with small budgets and inadequate staffing, and they fall behind the cutting edge of new technologies. This limits their group’s efficiency and effectiveness, and makes it difficult to have the kind of impact they would like.

However, there is growing interest in artificial intelligence (AI), machine learning (ML), and data analytics in non-profit organizations. Below are some of the many examples of non-profits using emerging technologies to handle finance, human resources, communications, internal operations, and sustainability.

FINANCE

Fraud and corruption are major challenges for any kind of organization as it is hard to monitor every financial transaction and business contract. AI tools can help managers automatically detect actions that warrant additional investigation. Businesses long have used AI and ML to create early warning systems, spot abnormalities, and thereby minimize financial misconduct. These tools offer ways to combat fraud and detect unusual transactions.

HUMAN RESOURCES

Advanced software helps organizations advertise, screen, and hire promising staff members. Once managers have decided what qualities they are seeking, AI can match applicants with employers. Automated systems can pre-screen resumes, check for relevant experience and skills, and identify applicants who are best suited for particular organizations. They also can weed out those who lack the required skills or do not pass basic screening criteria.

COMMUNICATIONS

Every non-profit faces challenges in terms of communications. In a rapidly-changing world, it is hard to keep in touch with outside donors, internal staff, and interested individuals. Chatbots automate conversations for commonly asked questions through text messaging. These tools can help with customer service and routine requests such as how to contribute money, address a budget question, or learn about upcoming programs. They represent an efficient and effective way to communicate with internal and external audiences….(More)”.

Six or Seven Things Social Media Can Do For Democracy

Curated on June 6, 2018August 3, 2018 by Stefaan Verhulst

Ethan Zuckerman: “I am concerned that we’ve not had a robust conversation about what we want social media to do for us.

We know what social media does for platform companies like Facebook and Twitter: it generates enormous masses of user-generated content that can be monetized with advertising, and reams of behavioral data that make that advertising more valuable. Perhaps we have a sense for what social media does for us as individuals, connecting us to distant friends, helping us maintain a lightweight awareness of each other’s lives even when we are not co-present. Or perhaps it’s a machine for disappointment and envy, a window into lives better lived than our own. It’s likely that what social media does for us personally is a deeply idiosyncratic question, dependent on our own lives, psyches and decisions, better discussed with our therapists than spoken about in generalities.

I’m interested in what social media should do for us as citizens in a democracy. We talk about social media as a digital public sphere, invoking Habermas and coffeehouses frequented by the bourgeoisie. Before we ask whether the internet succeeds as a public sphere, we ought to ask whether that’s actually what we want it to be.

I take my lead here from journalism scholar Michael Schudson, who took issue with a hyperbolic statement made by media critic James Carey: “journalism as a practice is unthinkable except in the context of democracy; in fact, journalism is usefully understood as another name for democracy.” For Schudson, this was a step too far. Journalism may be necessary for democracy to function well, but journalism by itself is not democracy and cannot produce democracy. Instead, we should work to understand the “Six or Seven Things News Can Do for Democracy”, the title of an incisive essay Schudson wrote to anchor his book, Why Democracies Need an Unloveable Press….

In this same spirit, I’d like to suggest six or seven things social media can do for democracy. I am neither as learned or as wise as Schudson, so I fully expect readers to offer half a dozen functions that I’ve missed. In the spirit of Schudson’s public forum and Benkler’s digital public sphere, I offer these in the hopes of starting, not ending, a conversation.

Social media can inform us…

Social media can amplify important voices and issues…

Social media can be a tool for connection and solidarity…

Social media can be a space for mobilization…

Social media can be a space for deliberation and debate…

Social media can be a tool for showing us a diversity of views and perspectives…

Social media can be a model for democratically governed spaces…(More).

NZ to perform urgent algorithm ‘stocktake’ fearing data misuse within government

Curated on June 5, 2018August 3, 2018 by Stefaan Verhulst

Asha McLean at ZDNet: “The New Zealand government has announced it will be assessing how government agencies are using algorithms to analyse data, hoping to ensure transparency and fairness in decisions that affect citizens.

A joint statement from Minister for Government Digital Services Clare Curran and Minister of Statistics James Shaw said the algorithm “stocktake” will be conducted with urgency, but cites only the growing interest in data analytics as the reason for the probe.

“The government is acutely aware of the need to ensure transparency and accountability as interest grows regarding the challenges and opportunities associated with emerging technology such as artificial intelligence,” Curran said.

It was revealed in April that Immigration New Zealand may have been using citizen data for less than desirable purposes, with claims that data collected through the country’s visa application process that was being used to determine those in breach of their visa conditions was in fact filtering people based on their age, gender, and ethnicity.

Rejecting the idea the data-collection project was racial profiling, Immigration Minister Iain Lees-Galloway told Radio New Zealand that Immigration looks at a range of issues, including at those who have made — and have had rejected — multiple visa applications.

“It looks at people who place the greatest burden on the health system, people who place the greatest burden on the criminal justice system, and uses that data to prioritise those people,” he said.

“It is important that we protect the integrity of our immigration system and that we use the resources that immigration has as effectively as we can — I do support them using good data to make good decisions about where best to deploy their resources.”

In the statement on Wednesday, Shaw pointed to two further data-modelling projects the government had embarked on, with one from the Ministry of Health looking into the probability of five-year post-transplant survival in New Zealand.

“Using existing data to help model possible outcomes is an important part of modern government decision-making,” Shaw said….(More)”.

Technology and satellite companies open up a world of data

Curated on June 5, 2018August 3, 2018 by Stefaan Verhulst

Gabriel Popkin at Nature: “In the past few years, technology and satellite companies’ offerings to scientists have increased dramatically. Thousands of researchers now use high-resolution data from commercial satellites for their work. Thousands more use cloud-computing resources provided by big Internet companies to crunch data sets that would overwhelm most university computing clusters. Researchers use the new capabilities to track and visualize forest and coral-reef loss; monitor farm crops to boost yields; and predict glacier melt and disease outbreaks. Often, they are analysing much larger areas than has ever been possible — sometimes even encompassing the entire globe. Such studies are landing in leading journals and grabbing media attention.

Commercial data and cloud computing are not panaceas for all research questions. NASA and the European Space Agency carefully calibrate the spectral quality of their imagers and test them with particular types of scientific analysis in mind, whereas the aim of many commercial satellites is to take good-quality, high-resolution pictures for governments and private customers. And no company can compete with Landsat’s free, publicly available, 46-year archive of images of Earth’s surface. For commercial data, scientists must often request images of specific regions taken at specific times, and agree not to publish raw data. Some companies reserve cloud-computing assets for researchers with aligned interests such as artificial intelligence or geospatial-data analysis. And although companies publicly make some funding and other resources available for scientists, getting access to commercial data and resources often requires personal connections. Still, by choosing the right data sources and partners, scientists can explore new approaches to research problems.

Mapping poverty

Joshua Blumenstock, an information scientist at the University of California, Berkeley (UCB), is always on the hunt for data he can use to map wealth and poverty, especially in countries that do not conduct regular censuses. “If you’re trying to design policy or do anything to improve living conditions, you generally need data to figure out where to go, to figure out who to help, even to figure out if the things you’re doing are making a difference.”

In a 2015 study, he used records from mobile-phone companies to map Rwanda’s wealth distribution (J. Blumenstock et al. Science 350, 1073–1076; 2015). But to track wealth distribution worldwide, patching together data-sharing agreements with hundreds of these companies would have been impractical. Another potential information source — high-resolution commercial satellite imagery — could have cost him upwards of US$10,000 for data from just one country….

Use of commercial images can also be restricted. Scientists are free to share or publish most government data or data they have collected themselves. But they are typically limited to publishing only the results of studies of commercial data, and at most a limited number of illustrative images.

Many researchers are moving towards a hybrid approach, combining public and commercial data, and running analyses locally or in the cloud, depending on need. Weiss still uses his tried-and-tested ArcGIS software from Esri for studies of small regions, and jumps to Earth Engine for global analyses.

The new offerings herald a shift from an era when scientists had to spend much of their time gathering and preparing data to one in which they’re thinking about how to use them. “Data isn’t an issue any more,” says Roy. “The next generation is going to be about what kinds of questions are we going to be able to ask?”…(More)”.

To Lose (But your Chains): Using Blockchain To Better Humanity

Curated on June 5, 2018August 3, 2018 by Stefaan Verhulst

Key findings of report by Asheem Singh:

“Like the internet before it, blockchain has the potential to revolutionise the charity sector. It offers huge but as yet untapped benefits to charities – from ensuring the right recipients receive what they are due, to modernising charitable giving and offering donors real-time visibility of where their funds are being spent and what impact it’s having.
Despite the potential benefits, the charity sector is currently behind the curve on blockchain technology. There are currently too few examples of blockchain use in the charity sector. The sector urgently needs to engage with the technology, given that it is revolutionising sectors – like banking – that charities already rely on.
Blockchain is no silver bullet for all of the problems facing the charity sector. True, blockchain offers new perspectives on the challenges facing the sector, from transparency and efficiency to governance and accountability. But it does not hold all the answers. For example, although the technology can improve the efficiency and transparency of payment-byresults, it does nothing to address the wellknown issues with that model.
Blockchain cannot replace the key role of ‘charity leader’, who has to define what is “right” and where money should be spent. Day to day, charity leaders are responsible for making tough decisions about resource allocation. They often possess knowledge that donors do not. Remove charities as the intermediaries between donor and recipient – which blockchain threatens – and the issues around securing core cost funding would only be exacerbated.
The technology also presents new pitfalls that need to be considered before charities jump on the bandwagon. Most notably, initiatives that have sought to bridge the charity sector with blockchain have been vulnerable to hackers. Charities should be well aware of the challenges of new technologies and make sure they are working with technologists to overcome them.
On its current trajectory, the future of charitable action is developing without the input of charities. Technologists are leading the conversation, yet they do not have the in depth understanding of the problems facing the charity sector or those they help. Some even see charities as the problem to be solved….(More)”.

Bonding with Your Algorithm

Curated on June 5, 2018August 3, 2018 by Stefaan Verhulst

Conversation with Nicolas Berggruen at the Edge: “The relationship between parents and children is the most important relationship. It gets more complicated in this case because, beyond the children being our natural children, we can influence them even beyond. We can influence them biologically, and we can use artificial intelligence as a new tool. I’m not a scientist or a technologist whatsoever, but the tools of artificial intelligence, in theory, are algorithm- or computer-based. In reality, I would argue that even an algorithm is biological because it comes from somewhere. It doesn’t come from itself. If it’s related to us as creators or as the ones who are, let’s say, enabling the algorithms, well, we’re the parents.

Who are those children that we are creating? What do we want them to be like as part of the earth, compared to us as a species and, frankly, compared to us as parents? They are our children. We are the parents. How will they treat us as parents? How do we treat our own parents? How do we treat our children? We have to think of these in the exact same way. Separating technology and humans the way we often think about these issues is almost wrong. If it comes from us, it’s the same thing. We have a responsibility. We have the power and the imagination to shape this future generation. It’s exciting, but let’s just make sure that they view us as their parents. If they view us as their parents, we will have a connection….(More)”

A Rule of Persons, Not Machines: The Limits of Legal Automation

Curated on June 5, 2018August 3, 2018 by Stefaan Verhulst

Paper by Frank A. Pasquale: “For many legal futurists, attorneys’ work is a prime target for automation. They view the legal practice of most businesses as algorithmic: data (such as facts) are transformed into outputs (agreements or litigation stances) via application of set rules. These technophiles promote substituting computer code for contracts and descriptions of facts now written by humans. They point to early successes in legal automation as proof of concept. TurboTax has helped millions of Americans file taxes, and algorithms have taken over certain aspects of stock trading. Corporate efforts to “formalize legal code” may bring new efficiencies in areas of practice characterized by both legal and factual clarity.

However, legal automation can also elide or exclude important human values, necessary improvisations, and irreducibly deliberative governance. Due process, appeals, and narratively intelligible explanation from persons, for persons, depend on forms of communication that are not reducible to software. Language is constitutive of these aspects of law. To preserve accountability and a humane legal order, these reasons must be expressed in language by a responsible person. This basic requirement for legitimacy limits legal automation in several contexts, including corporate compliance, property recordation, and contracting. A robust and ethical legal profession respects the flexibility and subtlety of legal language as a prerequisite for a just and accountable social order. It ensures a rule of persons, not machines…(More)”

Rational Inattention: A Disciplined Behavioral Model

Curated on June 5, 2018August 3, 2018 by Stefaan Verhulst

Paper by Bartosz Mackowiak, Filip Matejka and Mirko Wiederholt: “This survey paper argues that rational inattention matters. It is likely to become an important part of Economics, because it bridges a gap between classical economics and behavioral economics. Actions look behavioral, since agents cannot process all available information; yet agents optimize in the sense that they try to deal optimally with their cognitive limitations – hence the term ”rational inattention.” We show how rational inattention describes the adaptation of agents’ behavioral biases due to policy and other changes of the economic environment. Then, we survey the existing literature, and discuss what the unifying mechanisms behind the results in these papers are. Finally, we lay out implications for policy, and propose what we believe are the most fruitful steps for future research in this area. Economics is about adjustments to scarcity.

Rational inattention studies adjustments to scarcity of attention. Understanding how people summarize, filter, and digest the abundant available information is key to understanding many phenomena in economics. Several crucial findings in economics, even some whole subfields, have been built around the assumptions of imperfect or asymmetric information. However, nowadays, many more forms of information than ever before are available due to new technologies, yet we are able to digest little of it. Which form of imperfect information we possess and act upon is thus largely not determined by which information is given to us, but by which information we choose to attend to….(More)”.

New Technologies Won’t Reduce Scarcity, but Here’s Something That Might

Curated on June 5, 2018August 3, 2018 by Stefaan Verhulst

Vasilis Kostakis and Andreas Roos at the Harvard Business Review: “In a book titled Why Can’t We All Just Get Along?, MIT scientists Henry Lieberman and Christopher Fry discuss why we have wars, mass poverty, and other social ills. They argue that we cannot cooperate with each other to solve our major problems because our institutions and businesses are saturated with a competitive spirit. But Lieberman and Fry have some good news: modern technology can address the root of the problem. They believe that we compete when there is scarcity, and that recent technological advances, such as 3D printing and artificial intelligence, will end widespread scarcity. Thus, a post-scarcity world, premised on cooperation, would emerge.

But can we really end scarcity?

We believe that the post-scarcity vision of the future is problematic because it reflects an understanding of technology and the economy that could worsen the problems it seeks to address. This is the bad news. Here’s why:

New technologies come to consumers as finished products that can be exchanged for money. What consumers often don’t understand is that the monetary exchange hides the fact that many of these technologies exist at the expense of other humans and local environments elsewhere in the global economy….

The good news is that there are alternatives. The wide availability of networked computers has allowed new community-driven and open-source business models to emerge. For example, consider Wikipedia, a free and open encyclopedia that has displaced the Encyclopedia Britannica and Microsoft Encarta. Wikipedia is produced and maintained by a community of dispersed enthusiasts primarily driven by other motives than profit maximization. Furthermore, in the realm of software, see the case of GNU/Linux on which the top 500 supercomputers and the majority of websites run, or the example of the Apache Web Server, the leading software in the web-server market. Wikipedia, Apache and GNU/Linux demonstrate how non-coercive cooperation around globally-shared resources (i.e. a commons) can produce artifacts as innovative, if not more, as those produced by industrial capitalism.

In the same way, the emergence of networked micro-factories are giving rise to new open-source business models in the realm of design and manufacturing. Such spaces can either be makerspaces, fab labs, or other co-working spaces, equipped with local manufacturing technologies, such as 3D printing and CNC machines or traditional low-tech tools and crafts. Moreover, such spaces often offer collaborative environments where people can meet in person, socialize and co-create.

This is the context in which a new mode of production is emerging. This mode builds on the confluence of the digital commons of knowledge, software, and design with local manufacturing technologies. It can be codified as “design global, manufacture local” following the logic that what is light (knowledge, design) becomes global, while what is heavy (machinery) is local, and ideally shared. Design global, manufacture local (DGML) demonstrates how a technology project can leverage the digital commons to engage the global community in its development, celebrating new forms of cooperation. Unlike large-scale industrial manufacturing, the DGML model emphasizes application that is small-scale, decentralized, resilient, and locally controlled. DGML could recognize the scarcities posed by finite resources and organize material activities accordingly. First, it minimizes the need to ship materials over long distances, because a considerable part of the manufacturing takes place locally. Local manufacturing also makes maintenance easier, and also encourages manufacturers to design products to last as long as possible. Last, DGML optimizes the sharing of knowledge and design as there are no patent costs to pay for….(More)”