What To Do With The Urban Spaces Technology Makes Obsolete

Curated on Posted on by Stefaan Verhulst

Peter Madden at the Huffington Post: “Digital tech will make many city spaces redundant: artificial intelligence doesn’t care where it works; autonomous vehicles don’t care they where they park. These spaces must be repurposed for cities to thrive in the future….

This is an opportunity to ask what people want from their cities and how redundant spaces can meet these needs.

There have been multiple academic studies and marketing surveys on this, and they boil down to two main things. Citizens first want the basics: employment opportunities, affordable housing, good transport, and safe streets. Further up the hierarchy of needs, they also care about the physical appearance of the city, including the availability of parks and green spaces, the feel of the city in terms of openness, diversity and social interaction, and the experience in the city whether that’s tasting new foods, buying an unexpected gift, or discovering a new band.

Re-Greening

The places that were once reserved for cars can be spaces for pedestrians and bike lanes, with walkable and cycle-friendly cities offering cheaper transit, healthier citizens, and stronger communities. Greenery could flourish, with new parks, trees and allotments providing access to nature, sponges to absorb flood-water and urban cooling in a warming world.

Flexible Working

Who really wants a lengthy commute to a regimented workplace? Future office spaces will harness new technology to help people work flexibly, collaboratively and from multiple locations. When they do travel into the city centre office, this will be oriented around the experience of the individual employee, beautifully designed, technologically responsive, with different spaces for how they work best at different times of the day and on different tasks.

Making in Cities

The 4th industrial revolution allows manufacturing to return to urban centres for just-in-time, on demand and hyper-personalised production. Some ‘on-shoring’ is already happening, with McLaren car chassis, Clarks boots and Frog bikes being made again in British towns again. Data analytics, virtual reality, new materials, robotics and 3D printing will make it possible to produce or customise things on the high-street, right where the consumer wants them.

Affordable Housing

Unused buildings and empty land will be filled by new types of housing. In my home city, Bristol, a redundant building in a parade of shops is being turned into living space for the homeless, AEOB will ‘buy and convert empty offices into homes for people’, and ‘We Can Make’ is offering affordable prefabricated houses for empty urban plots. Housing innovations like this are springing up in cities across the world….(More)”.

The Efficiency Paradox: What Big Data Can’t Do

Curated on Posted on by Stefaan Verhulst

Book by Edward Tenner: “A bold challenge to our obsession with efficiency–and a new understanding of how to benefit from the powerful potential of serendipity

Algorithms, multitasking, the sharing economy, life hacks: our culture can’t get enough of efficiency. One of the great promises of the Internet and big data revolutions is the idea that we can improve the processes and routines of our work and personal lives to get more done in less time than we ever have before. There is no doubt that we’re performing at higher levels and moving at unprecedented speed, but what if we’re headed in the wrong direction?

Melding the long-term history of technology with the latest headlines and findings of computer science and social science, The Efficiency Paradox questions our ingrained assumptions about efficiency, persuasively showing how relying on the algorithms of digital platforms can in fact lead to wasted efforts, missed opportunities, and above all an inability to break out of established patterns. Edward Tenner offers a smarter way of thinking about efficiency, revealing what we and our institutions, when equipped with an astute combination of artificial intelligence and trained intuition, can learn from the random and unexpected….(More)”

How Artificial Intelligence Could Increase the Risk of Nuclear War

Curated on Posted on by Stefaan Verhulst

Rand Corporation: “The fear that computers, by mistake or malice, might lead humanity to the brink of nuclear annihilation has haunted imaginations since the earliest days of the Cold War.

The danger might soon be more science than fiction. Stunning advances in AI have created machines that can learn and think, provoking a new arms race among the world’s major nuclear powers. It’s not the killer robots of Hollywood blockbusters that we need to worry about; it’s how computers might challenge the basic rules of nuclear deterrence and lead humans into making devastating decisions.

That’s the premise behind a new paper from RAND Corporation, How Might Artificial Intelligence Affect the Risk of Nuclear War? It’s part of a special project within RAND, known as Security 2040, to look over the horizon and anticipate coming threats.

“This isn’t just a movie scenario,” said Andrew Lohn, an engineer at RAND who coauthored the paper and whose experience with AI includes using it to route drones, identify whale calls, and predict the outcomes of NBA games. “Things that are relatively simple can raise tensions and lead us to some dangerous places if we are not careful.”…(More)”.

How artificial intelligence is transforming the world

Curated on Posted on by Stefaan Verhulst

Report by Darrell West and John Allen at Brookings: “Most people are not very familiar with the concept of artificial intelligence (AI). As an illustration, when 1,500 senior business leaders in the United States in 2017 were asked about AI, only 17 percent said they were familiar with it. A number of them were not sure what it was or how it would affect their particular companies. They understood there was considerable potential for altering business processes, but were not clear how AI could be deployed within their own organizations.

Despite its widespread lack of familiarity, AI is a technology that is transforming every walk of life. It is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decisionmaking. Our hope through this comprehensive overview is to explain AI to an audience of policymakers, opinion leaders, and interested observers, and demonstrate how AI already is altering the world and raising important questions for society, the economy, and governance.

In this paper, we discuss novel applications in finance, national security, health care, criminal justice, transportation, and smart cities, and address issues such as data access problems, algorithmic bias, AI ethics and transparency, and legal liability for AI decisions. We contrast the regulatory approaches of the U.S. and European Union, and close by making a number of recommendations for getting the most out of AI while still protecting important human values.

In order to maximize AI benefits, we recommend nine steps for going forward:

  • Encourage greater data access for researchers without compromising users’ personal privacy,
  • invest more government funding in unclassified AI research,
  • promote new models of digital education and AI workforce development so employees have the skills needed in the 21st-century economy,
  • create a federal AI advisory committee to make policy recommendations,
  • engage with state and local officials so they enact effective policies,
  • regulate broad AI principles rather than specific algorithms,
  • take bias complaints seriously so AI does not replicate historic injustice, unfairness, or discrimination in data or algorithms,
  • maintain mechanisms for human oversight and control, and
  • penalize malicious AI behavior and promote cybersecurity….(More)

Table of Contents
I. Qualities of artificial intelligence
II. Applications in diverse sectors
III. Policy, regulatory, and ethical issues
IV. Recommendations
V. Conclusion

Artificial Unintelligence

Curated on Posted on by Stefaan Verhulst

Book by Meredith Broussard: “A guide to understanding the inner workings and outer limits of technology and why we should never assume that computers always get it right.

In Artificial Unintelligence, Meredith Broussard argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitally—hiring, driving, paying bills, even choosing romantic partners—that we have stopped demanding that our technology actually work. Broussard, a software developer and journalist, reminds us that there are fundamental limits to what we can (and should) do with technology. With this book, she offers a guide to understanding the inner workings and outer limits of technology—and issues a warning that we should never assume that computers always get things right.

Making a case against technochauvinism—the belief that technology is always the solution—Broussard argues that it’s just not true that social problems would inevitably retreat before a digitally enabled Utopia. To prove her point, she undertakes a series of adventures in computer programming. She goes for an alarming ride in a driverless car, concluding “the cyborg future is not coming any time soon”; uses artificial intelligence to investigate why students can’t pass standardized tests; deploys machine learning to predict which passengers survived the Titanic disaster; and attempts to repair the U.S. campaign finance system by building AI software. If we understand the limits of what we can do with technology, Broussard tells us, we can make better choices about what we should do with it to make the world better for everyone…(More)”.

Leveraging the Power of Bots for Civil Society

Curated on Posted on by Stefaan Verhulst

Allison Fine & Beth Kanter  at the Stanford Social Innovation Review: “Our work in technology has always centered around making sure that people are empowered, healthy, and feel heard in the networks within which they live and work. The arrival of the bots changes this equation. It’s not enough to make sure that people are heard; we now have to make sure that technology adds value to human interactions, rather than replacing them or steering social good in the wrong direction. If technology creates value in a human-centered way, then we will have more time to be people-centric.

So before the bots become involved with almost every facet of our lives, it is incumbent upon those of us in the nonprofit and social-change sectors to start a discussion on how we both hold on to and lead with our humanity, as opposed to allowing the bots to lead. We are unprepared for this moment, and it does not feel like an understatement to say that the future of humanity relies on our ability to make sure we’re in charge of the bots, not the other way around.

To Bot or Not to Bot?

History shows us that bots can be used in positive ways. Early adopter nonprofits have used bots to automate civic engagement, such as helping citizens register to vote, contact their elected officials, and elevate marginalized voices and issues. And nonprofits are beginning to use online conversational interfaces like Alexa for social good engagement. For example, the Audubon Society has released an Alexa skill to teach bird calls.

And for over a decade, Invisible People founder Mark Horvath has been providing “virtual case management” to homeless people who reach out to him through social media. Horvath says homeless agencies can use chat bots programmed to deliver basic information to people in need, and thus help them connect with services. This reduces the workload for case managers while making data entry more efficient. He explains it working like an airline reservation: The homeless person completes the “paperwork” for services by interacting with a bot and then later shows their ID at the agency. Bots can greatly reduce the need for a homeless person to wait long hours to get needed services. Certainly this is a much more compassionate use of bots than robot security guards who harass homeless people sleeping in front of a business.

But there are also examples where a bot’s usefulness seems limited. A UK-based social service charity, Mencap, which provides support and services to children with learning disabilities and their parents, has a chatbot on its website as part of a public education effort called #HereIAm. The campaign is intended to help people understand more about what it’s like having a learning disability, through the experience of a “learning disabled” chatbot named Aeren. However, this bot can only answer questions, not ask them, and it doesn’t become smarter through human interaction. Is this the best way for people to understand the nature of being learning disabled? Is it making the difficulties feel more or less real for the inquirers? It is clear Mencap thinks the interaction is valuable, as they reported a 3 percent increase in awareness of their charity….

The following discussion questions are the start of conversations we need to have within our organizations and as a sector on the ethical use of bots for social good:

  • What parts of our work will benefit from greater efficiency without reducing the humanness of our efforts? (“Humanness” meaning the power and opportunity for people to learn from and help one another.)
  • Do we have a privacy policy for the use and sharing of data collected through automation? Does the policy emphasize protecting the data of end users? Is the policy easily accessible by the public?
  • Do we make it clear to the people using the bot when they are interacting with a bot?
  • Do we regularly include clients, customers, and end users as advisors when developing programs and services that use bots for delivery?
  • Should bots designed for service delivery also have fundraising capabilities? If so, can we ensure that our donors are not emotionally coerced into giving more than they want to?
  • In order to truly understand our clients’ needs, motivations, and desires, have we designed our bots’ conversational interactions with empathy and compassion, or involved social workers in the design process?
  • Have we planned for weekly checks of the data generated by the bots to ensure that we are staying true to our values and original intentions, as AI helps them learn?….(More)”.

UK can lead the way on ethical AI, says Lords Committee

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Lords Select Committee: “The UK is in a strong position to be a world leader in the development of artificial intelligence (AI). This position, coupled with the wider adoption of AI, could deliver a major boost to the economy for years to come. The best way to do this is to put ethics at the centre of AI’s development and use concludes a report by the House of Lords Select Committee on Artificial Intelligence, AI in the UK: ready, willing and able?, published today….

One of the recommendations of the report is for a cross-sector AI Code to be established, which can be adopted nationally, and internationally. The Committee’s suggested five principles for such a code are:

  1. Artificial intelligence should be developed for the common good and benefit of humanity.
  2. Artificial intelligence should operate on principles of intelligibility and fairness.
  3. Artificial intelligence should not be used to diminish the data rights or privacy of individuals, families or communities.
  4. All citizens should have the right to be educated to enable them to flourish mentally, emotionally and economically alongside artificial intelligence.
  5. The autonomous power to hurt, destroy or deceive human beings should never be vested in artificial intelligence.

Other conclusions from the report include:

  • Many jobs will be enhanced by AI, many will disappear and many new, as yet unknown jobs, will be created. Significant Government investment in skills and training will be necessary to mitigate the negative effects of AI. Retraining will become a lifelong necessity.
  • Individuals need to be able to have greater personal control over their data, and the way in which it is used. The ways in which data is gathered and accessed needs to change, so that everyone can have fair and reasonable access to data, while citizens and consumers can protect their privacy and personal agency. This means using established concepts, such as open data, ethics advisory boards and data protection legislation, and developing new frameworks and mechanisms, such as data portability and data trusts.
  • The monopolisation of data by big technology companies must be avoided, and greater competition is required. The Government, with the Competition and Markets Authority, must review the use of data by large technology companies operating in the UK.
  • The prejudices of the past must not be unwittingly built into automated systems. The Government should incentivise the development of new approaches to the auditing of datasets used in AI, and also to encourage greater diversity in the training and recruitment of AI specialists.
  • Transparency in AI is needed. The industry, through the AI Council, should establish a voluntary mechanism to inform consumers when AI is being used to make significant or sensitive decisions.
  • At earlier stages of education, children need to be adequately prepared for working with, and using, AI. The ethical design and use of AI should become an integral part of the curriculum.
  • The Government should be bold and use targeted procurement to provide a boost to AI development and deployment. It could encourage the development of solutions to public policy challenges through speculative investment. There have been impressive advances in AI for healthcare, which the NHS should capitalise on.
  • It is not currently clear whether existing liability law will be sufficient when AI systems malfunction or cause harm to users, and clarity in this area is needed. The Committee recommend that the Law Commission investigate this issue.
  • The Government needs to draw up a national policy framework, in lockstep with the Industrial Strategy, to ensure the coordination and successful delivery of AI policy in the UK….(More)”.

Blockchain Slashes US Govt. Contract Award Time From 100 To 10 Days

Curated on Posted on by Stefaan Verhulst

Article by Cameron Bishop: “…The US General services Administration built the first federal procurement blockchain proof of concept about six months ago. The procurement blockchain was built to demonstrate how the distributed ledger technology can modernize federal procurement. The pilot project made them realize that blockchain, when combined with artificial intelligence and robotics, provides the foundational architecture for widespread automation.

The proof of concept, which was built in seven weeks, automated the procurement process. More importantly, it reduced the average contract award time from 100 days to less than 10 days. Complex tasks such as financial review was automated through the use of blockchain. It also eliminated human error, bias and subjectivity from the process. A smart contract deployed in the blockchain automatically calculated the financial health score from the offerors’ balance sheets and income statements. The entire process was standardized using commercial and government practices.

Furthermore, the use of blockchain ledger ensured that vendors were kept abreast of the developments. Vendors received alerts on a real-time basis as the offers progress through the workflow. This made the process transparent, while preserving the privacy of each transaction. The success of this pilot project is expected to bring a drastic change in the federal procurement process.

While a blockchain can be public, permissioned, and private, federal agencies may opt for a private blockchain to facilitate procurement transactions among pre-screened vendors with digital identity certificates.

The Federal Acquisition Regulation (FAR) provides guidelines to ensure integrity, openness and fairness in federal procurement. The blockchain technology will enforce those policies through a system of procedural trust embedded into the platform.

By using blockchain technology, the federal procurement process can be more transparent, efficient, faster, and less vulnerable to fraud and abuse. More importantly, by design, a blockchain preserves the integrity of the assets and transactions between multiple parties within the value chain. Additionally, blockchain will avoid unnecessary litigations, while promoting competition in a healthy manner. It will also provide an organization with unique insights into the procurement value chain unavailable previously….(More)”.

Algorithmic Impact Assessment (AIA) framework

Curated on Posted on by Stefaan Verhulst

Report by AINow Institute: “Automated decision systems are currently being used by public agencies, reshaping how criminal justice systems work via risk assessment algorithms1 and predictive policing, optimizing energy use in critical infrastructure through AI-driven resource allocation, and changing our employment4 and educational systems through automated evaluation tools and matching algorithms.Researchers, advocates, and policymakers are debating when and where automated decision systems are appropriate, including whether they are appropriate at all in particularly sensitive domains.

Questions are being raised about how to fully assess the short and long term impacts of these systems, whose interests they serve, and if they are sufficiently sophisticated to contend with complex social and historical contexts. These questions are essential, and developing strong answers has been hampered in part by a lack of information and access to the systems under deliberation. Many such systems operate as “black boxes” – opaque software tools working outside the scope of meaningful scrutiny and accountability.8 This is concerning, since an informed policy debate is impossible without the ability to understand which existing systems are being used, how they are employed, and whether these systems cause unintended consequences. The Algorithmic Impact Assessment (AIA) framework proposed in this report is designed to support affected communities and stakeholders as they seek to assess the claims made about these systems, and to determine where – or if – their use is acceptable….

KEY ELEMENTS OF A PUBLIC AGENCY ALGORITHMIC IMPACT ASSESSMENT

1. Agencies should conduct a self-assessment of existing and proposed automated decision systems, evaluating potential impacts on fairness, justice, bias, or other concerns across affected communities;

2. Agencies should develop meaningful external researcher review processes to discover, measure, or track impacts over time;

3. Agencies should provide notice to the public disclosing their definition of “automated decision system,” existing and proposed systems, and any related self-assessments and researcher review processes before the system has been acquired;

4. Agencies should solicit public comments to clarify concerns and answer outstanding questions; and

5. Governments should provide enhanced due process mechanisms for affected individuals or communities to challenge inadequate assessments or unfair, biased, or otherwise harmful system uses that agencies have failed to mitigate or correct….(More)”.

AI And Open Data Show Just How Often Cars Block Bus And Bike Lanes

Curated on Posted on by Stefaan Verhulst

Eillie Anzilotti in Fast Company: “…While anyone who bikes or rides a bus in New York City knows intuitively that the lanes are often blocked, there’s been little data to back up that feeling apart from the fact that last year, the NYPD issues 24,000 tickets for vehicles blocking bus lanes, and around 79,000 to cars in the bike lane. By building the algorithm, Bell essentializes what engaged citizenship and productive use of open data looks like. The New York City Department of Transportation maintains several hundred video cameras throughout the city; those cameras feed images in real time to the DOT’s open-data portal. Bell downloaded a week’s worth of footage from that portal to analyze.

To build his computer algorithm to do the analysis, he fed around 2,000 images of buses, cars, pedestrians, and vehicles like UPS trucks into TensorFlow, Google’s open-source framework that the tech giant is using to train autonomous vehicles to recognize other road users. “Because of the push into AVs, machine learning in general and neural networks have made lots of progress, because they have to answer the same questions of: What is this vehicle, and what is it going to do?” Bell says. After several rounds of processing, Bell was able to come up with an algorithm that fairly faultlessly could determine if a vehicle at the bus stop was, in fact, a bus, or if it was something else that wasn’t supposed to be there.

As cities and governments, spurred by organizations like OpenGov, have moved to embrace transparency and open data, the question remains: So, what do you do with it?

For Bell, the answer is that citizens can use it to empower themselves. “I’m a little uncomfortable with cameras and surveillance in cities,” Bell says. “But agencies like the NYPD and DOT have already made the decision to put the cameras up. We don’t know the positive and negative outcomes if more and more data from cameras is opened to the public, but if the cameras are going in, we should know what data they’re collecting and be able to access it,” he says. He’s made his algorithm publicly available in the hopes that more people will use data to investigate the issue on their own streets, and perhaps in other cities….Bell is optimistic that open data can empower more citizens to identify issues in their own cities and bring a case for why they need to be addressed….(More)”.