Smart Cities: Digital Solutions for a More Livable Future


Report by the McKinsey Global Institute (MGI): “After a decade of experimentation, smart cities are entering a new phase. Although they are only one part of the full tool kit for making a city great, digital solutions are the most powerful and cost-effective additions to that tool kit in many years. This report analyzes dozens of current applications and finds that cities could use them to improve some quality-of-life indicators by 10–30 percent.It also finds that even the most cutting-edge smart cities on the planet are still at the beginning of their journey. ƒ

Smart cities add digital intelligence to existing urban systems, making it possible to do more with less. Connected applications put real-time, transparent information into the hands of users to help them make better choices. These tools can save lives, prevent crime, and reduce the disease burden. They can save time, reduce waste, and even help boost social connectedness. When cities function more efficiently, they also become more productive places to do business. ƒ

MGI assessed how dozens of current smart city applications could perform in three sample cities with varying legacy infrastructure systems and baseline starting points. We found that these tools could reduce fatalities by 8–10 percent, accelerate emergency response times by 20–35 percent, shave the average commute by 15–20 percent, lower the disease burden by 8–15 percent, and cut greenhouse gas emissions by 10–15 percent, among other positive outcomes. ƒ

Our snapshot of deployment in 50 cities around the world shows that wealthier urban areas are generally transforming faster, although many have low public awareness and usage of the applications they have implemented. Asian megacities, with their young populations of digital natives and big urban problems to solve, are achieving exceptionally high adoption. Measured against what is possible today, even the global leaders have more work to do in building out the technology base, rolling out the full range of possible applications, and boosting adoption and user satisfaction. Many cities have not yet implemented some of the applications that could have the biggest potential impact. Since technology never stands still, the bar will only get higher. ƒ

The public sector would be the natural owner of 70 percent of the applications we examined. But 60 percent of the initial investment required to implement the full range of applications could come from private actors. Furthermore, more than half of the initial investment made by the public sector could generate a positive return, whether in direct savings or opportunities to produce revenue. ƒ

The technologies analyzed in this report can help cities make moderate or significant progress toward 70 percent of the Sustainable Development Goals. Yet becoming a smart city is less effective as an economic development strategy for job creation. ƒ Smart cities may disrupt some industries even as they present substantial market opportunities. Customer needs will force a reevaluation of current products and services to meet higher expectations of quality, cost, and efficiency in everything from mobility to healthcare.

Smart city solutions will shift value across the landscape of cities and throughout value chains. Companies looking to enter smart city markets will need different skill sets, creative financing models, and a sharper focus on civic engagement.

Becoming a smart city is not a goal but a means to an end. The entire point is to respond more effectively and dynamically to the needs and desires of residents. Technology is simply a tool to optimize the infrastructure, resources, and spaces they share. Few cities want to lag behind, but it is critical not to get caught up in technology for its own sake. Smart cities need to focus on improving outcomes for residents and enlisting their active participation in shaping the places they call home….(More)”.

Blockchain Ethical Design Framework


Report by Cara LaPointe and Lara Fishbane: “There are dramatic predictions about the potential of blockchain to “revolutionize” everything from worldwide financial markets and the distribution of humanitarian assistance to the very way that we outright recognize human identity for billions of people around the globe. Some dismiss these claims as excessive technology hype by citing flaws in the technology or robustness of incumbent solutions and infrastructure.

The reality will likely fall somewhere between these two extremes across multiple sectors. Where initial applications of blockchain were focused on the financial industry, current applications have rapidly expanded to address a wide array of sectors with major implications for social impact.

This paper aims to demonstrate the capacity of blockchain to create scalable social impact and to identify the elements that need to be addressed to mitigate challenges in its application. We are at a moment when technology is enabling society to experiment with new solutions and business models. Ubiquity and global reach, increased capabilities, and affordability have made technology a critical tool for solving problems, making this an exciting time to think about achieving greater social impact. We can address issues for underserved or marginalized people in ways that were previously unimaginable.

Blockchain is a technology that holds real promise for dealing with key inefficiencies and transforming operations in the social sector and for improving lives. Because of its immutability and decentralization, blockchain has the potential to create transparency, provide distributed verification, and build trust across multiple systems. For instance, blockchain applications could provide the means for establishing identities for individuals without identification papers, improving access to finance and banking services for underserved populations, and distributing aid to refugees in a more transparent and efficient manner. Similarly, national and subnational governments are putting land registry information onto blockchains to create greater transparency and avoid corruption and manipulation by third parties.

From increasing access to capital, to tracking health and education data across multiple generations, to improving voter records and voting systems, blockchain has countless potential applications for social impact. As developers take on building these types of solutions, the social effects of blockchain can be powerful and lasting. With the potential for such a powerful impact, the design, application, and approach to the development and implementation of blockchain technologies have long-term implications for society and individuals.

This paper outlines why intentionality of design, which is important with any technology, is particularly crucial with blockchain, and offers a framework to guide policymakers and social impact organizations. As social media, cryptocurrencies, and algorithms have shown, technology is not neutral. Values are embedded in the code. How the problem is defined and by whom, who is building the solution, how it gets programmed and implemented, who has access, and what rules are created have consequences, in intentional and unintentional ways. In the applications and implementation of blockchain, it is critical to understand that seemingly innocuous design choices have resounding ethical implications on people’s lives.

This white paper addresses why intentionality of design matters, identifies the key questions that should be asked, and provides a framework to approach use of blockchain, especially as it relates to social impact. It examines the key attributes of blockchain, its broad applicability as well as its particular potential for social impact, and the challenges in fully realizing that potential. Social impact organizations and policymakers have an obligation to understand the ethical approaches used in designing blockchain technology, especially how they affect marginalized and vulnerable populations….(More)”

Can Smart Cities Be Equitable?


Homi Kharas and Jaana Remes at Project Syndicate: “Around the world, governments are making cities “smarter” by using data and digital technology to build more efficient and livable urban environments. This makes sense: with urban populations growing and infrastructure under strain, smart cities will be better positioned to manage rapid change.

But as digital systems become more pervasive, there is a danger that inequality will deepen unless local governments recognize that tech-driven solutions are as important to the poor as they are to the affluent.

While offline populations can benefit from applications running in the background of daily life – such as intelligent signals that help with traffic flows – they will not have access to the full range of smart-city programs. With smartphones serving as the primary interface in the modern city, closing the digital divide, and extending access to networks and devices, is a critical first step.

City planners can also deploy technology in ways that make cities more inclusive for the poor, the disabled, the elderly, and other vulnerable people. Examples are already abundant.

In New York City, the Mayor’s Public Engagement Unit uses interagency data platforms to coordinate door-to-door outreachto residents in need of assistance. In California’s Santa Clara County, predictive analytics help prioritize shelter space for the homeless. On the London Underground, an app called Wayfindr uses Bluetooth to help visually impaired travelers navigate the Tube’s twisting pathways and escalators.

And in Kolkata, India, a Dublin-based startup called Addressing the Unaddressedhas used GPS to provide postal addresses for more than 120,000 slum dwellers in 14 informal communities. The goal is to give residents a legal means of obtaining biometric identification cards, essential documentation needed to access government services and register to vote.

But while these innovations are certainly significant, they are only a fraction of what is possible.

Public health is one area where small investments in technology can bring big benefits to marginalized groups. In the developing world, preventable illnesses comprise a disproportionate share of the disease burden. When data are used to identify demographic groups with elevated risk profiles, low-cost mobile-messaging campaigns can transmit vital prevention information. So-called “m-health” interventions on issues like vaccinations, safe sex, and pre- and post-natal care have been shown to improve health outcomes and lower health-care costs.

Another area ripe for innovation is the development of technologies that directly aid the elderly….(More)”.

We Need to Save Ignorance From AI


Christina Leuker and Wouter van den Bos in Nautilus:  “After the fall of the Berlin Wall, East German citizens were offered the chance to read the files kept on them by the Stasi, the much-feared Communist-era secret police service. To date, it is estimated that only 10 percent have taken the opportunity.

In 2007, James Watson, the co-discoverer of the structure of DNA, asked that he not be given any information about his APOE gene, one allele of which is a known risk factor for Alzheimer’s disease.

Most people tell pollsters that, given the choice, they would prefer not to know the date of their own death—or even the future dates of happy events.

Each of these is an example of willful ignorance. Socrates may have made the case that the unexamined life is not worth living, and Hobbes may have argued that curiosity is mankind’s primary passion, but many of our oldest stories actually describe the dangers of knowing too much. From Adam and Eve and the tree of knowledge to Prometheus stealing the secret of fire, they teach us that real-life decisions need to strike a delicate balance between choosing to know, and choosing not to.

But what if a technology came along that shifted this balance unpredictably, complicating how we make decisions about when to remain ignorant? That technology is here: It’s called artificial intelligence.

AI can find patterns and make inferences using relatively little data. Only a handful of Facebook likes are necessary to predict your personality, race, and gender, for example. Another computer algorithm claims it can distinguish between homosexual and heterosexual men with 81 percent accuracy, and homosexual and heterosexual women with 71 percent accuracy, based on their picture alone. An algorithm named COMPAS (Correctional Offender Management Profiling for Alternative Sanctions) can predict criminal recidivism from data like juvenile arrests, criminal records in the family, education, social isolation, and leisure activities with 65 percent accuracy….

Recently, though, the psychologist Ralph Hertwig and legal scholar Christoph Engel have published an extensive taxonomy of motives for deliberate ignorance. They identified two sets of motives, in particular, that have a particular relevance to the need for ignorance in the face of AI.

The first set of motives revolves around impartiality and fairness. Simply put, knowledge can sometimes corrupt judgment, and we often choose to remain deliberately ignorant in response. For example, peer reviews of academic papers are usually anonymous. Insurance companies in most countries are not permitted to know all the details of their client’s health before they enroll; they only know general risk factors. This type of consideration is particularly relevant to AI, because AI can produce highly prejudicial information….(More)”.

Personal Data v. Big Data: Challenges of Commodification of Personal Data


Maria Bottis and  George Bouchagiar in the Open Journal of Philosophy: “Any firm today may, at little or no cost, build its own infrastructure to process personal data for commercial, economic, political, technological or any other purposes. Society has, therefore, turned into a privacy-unfriendly environment. The processing of personal data is essential for multiple economically and socially useful purposes, such as health care, education or terrorism prevention. But firms view personal data as a commodity, as a valuable asset, and heavily invest in processing for private gains. This article studies the potential to subject personal data to trade secret rules, so as to ensure the users’ control over their data without limiting the data’s free movement, and examines some positive scenarios of attributing commercial value to personal data….(More)”.

Research Shows Political Acumen, Not Just Analytical Skills, is Key to Evidence-Informed Policymaking


Press Release: “Results for Development (R4D) has released a new study unpacking how evidence translators play a key and somewhat surprising role in ensuring policymakers have the evidence they need to make informed decisions. Translators — who can be evidence producers, policymakers, or intermediaries such as journalists, advocates and expert advisors — identify, filter, interpret, adapt, contextualize and communicate data and evidence for the purposes of policymaking.

The study, Translators’ Role in Evidence-Informed Policymaking, provides a better understanding of who translators are and how different factors influence translators’ ability to promote the use of evidence in policymaking. This research shows translation is an essential function and that, absent individuals or organizations taking up the translator role, evidence translation and evidence-informed policymaking often do not take place.

“We began this research assuming that translators’ technical skills and analytical prowess would prove to be among the most important factors in predicting when and how evidence made its way into public sector decision making,” Nathaniel Heller, executive vice president for integrated strategies at Results for Development, said. “Surprisingly, that turned out not to be the case, and other ‘soft’ skills play a far larger role in translators’ efficacy than we had imagined.”

Key findings include:

  • Translator credibility and reputation are crucial to the ability to gain access to policymakers and to promote the uptake of evidence.
  • Political savvy and stakeholder engagement are among the most critical skills for effective translators.
  • Conversely, analytical skills and the ability to adapt, transform and communicate evidence were identified as being less important stand-alone translator skills.
  • Evidence translation is most effective when initiated by those in power or when translators place those in power at the center of their efforts.

The study includes a definitional and theoretical framework as well as a set of research questions about key enabling and constraining factors that might affect evidence translators’ influence. It also focuses on two cases in Ghana and Argentina to validate and debunk some of the intellectual frameworks around policy translators that R4D and others in the field have already developed. The first case focuses on Ghana’s blue-ribbon commission formed by the country’s president in 2015, which was tasked with reviewing Ghana’s national health insurance scheme. The second case looks at Buenos Aires’ 2016 government-led review of the city’s right to information regime….(More)”.

Ontario is trying a wild experiment: Opening access to its residents’ health data


Dave Gershorn at Quartz: “The world’s most powerful technology companies have a vision for the future of healthcare. You’ll still go to your doctor’s office, sit in a waiting room, and explain your problem to someone in a white coat. But instead of relying solely on their own experience and knowledge, your doctor will consult an algorithm that’s been trained on the symptoms, diagnoses, and outcomes of millions of other patients. Instead of a radiologist reading your x-ray, a computer will be able to detect minute differences and instantly identify a tumor or lesion. Or at least that’s the goal.

AI systems like these, currently under development by companies including Google and IBM, can’t read textbooks and journals, attend lectures, and do rounds—they need millions of real life examples to understand all the different variations between one patient and another. In general, AI is only as good as the data it’s trained on, but medical data is exceedingly private—most developed countries have strict health data protection laws, such as HIPAA in the United States….

These approaches, which favor companies with considerable resources, are pretty much the only way to get large troves of health data in the US because the American health system is so disparate. Healthcare providers keep personal files on each of their patients, and can only transmit them to other accredited healthcare workers at the patient’s request. There’s no single place where all health data exists. It’s more secure, but less efficient for analysis and research.

Ontario, Canada, might have a solution, thanks to its single-payer healthcare system. All of Ontario’s health data exists in a few enormous caches under government control. (After all, the government needs to keep track of all the bills its paying.) Similar structures exist elsewhere in Canada, such as Quebec, but Toronto, which has become a major hub for AI research, wants to lead the charge in providing this data to businesses.

Until now, the only people allowed to study this data were government organizations or researchers who partnered with the government to study disease. But Ontario has now entrusted the MaRS Discovery District—a cross between a tech incubator and WeWork—to build a platform for approved companies and researchers to access this data, dubbed Project Spark. The project, initiated by MaRS and Canada’s University Health Network, began exploring how to share this data after both organizations expressed interest to the government about giving broader health data access to researchers and companies looking to build healthcare-related tools.

Project Spark’s goal is to create an API, or a way for developers to request information from the government’s data cache. This could be used to create an app for doctors to access the full medical history of a new patient. Ontarians could access their health records at any time through similar software, and catalog health issues as they occur. Or researchers, like the ones trying to build AI to assist doctors, could request a different level of access that provides anonymized data on Ontarians who meet certain criteria. If you wanted to study every Ontarian who had Alzheimer’s disease over the last 40 years, that data would only be authorization and a few lines of code away.

There are currently 100 companies lined up to get access to data, comprised of health records from Ontario’s 14 million residents. (MaRS won’t say who the companies are). …(More)”

Delivering for citizens: How to triple the success rate of government transformations


Report by Tera Allas et al: “An increase in the number of successful government transformations could help solve society’s greatest challenges, serve citizens better, and support the more productive use of public resources.

Governments around the world know that to deliver for citizens, they must transform the services they provide. Aging populations are putting huge pressure on health and social services; educational systems need to equip young people with the skills for a technology-driven world; and the changing shape of cities is creating new demands on infrastructure. Many government services do not meet citizens’ growing expectations. These trends are contributing to public discontent

Unfortunately, around 80 percent of government efforts to transform performance don’t fully meet their objectives—a key finding of a survey of nearly 3,000 public officials across 18 countries as part of a new study by the McKinsey Center for Government. The study also includes insights from 80 case studies, as well as 30 in-depth interviews with leaders who have personally led transformations in government. Between them, these leaders have more than 300 years of collective experience in what it takes to succeed.

The failure rate of government transformations is far too high. It represents a huge missed opportunity to tackle society’s greatest challenges more effectively, to give citizens better experiences with government, and to make more productive use of limited public resources. If governments around the world matched their most improved counterparts, they could save as much as $3.5 trillion a year by 2021 while maintaining today’s levels of service quality. Alternatively, they could release substantial funds for the services citizens most care about, while keeping overall government expenditure constant….(More)”.

The distributed power of smartphones for medical research


Adi Gaskell: “One of the more significant areas of promise in health technology is the ability for data to be generated by us as individuals, and for AI to provide insights based upon this live stream of lifestyle data.  An example of what’s possible comes via a project researchers at Imperial College London have undertaken with the Vodafone Foundation.

The project aims to tap into the power of users smartphones to crunch cancer related data whilst they sleep.  Such distributed computing projects have been popular for some time, but this is one of the first to utilize the power in our smartphones.

The rationale for the project is identical to that of the early distributed computing ventures, such as SETI@Home, which utilized spare computing resources to process data from space.  The average smartphone contains a huge amount of computing power that generally lies dormant over night.

Dream Lab

Users participate by downloading the DreamLab app onto their phone and run it for six hours overnight as the phone charges.  The sleep downloads a small packet of data overnight, with the processors in the phone then running millions of calculations, uploading the results to a central server, and clearing the data from the phone.

The app has already been used in Australia, with researchers using it to crunch data for pancreatic cancer, and is now ready to be used for the first time in Europe.  If they can secure 100,000 users running the app each night, the team can process as much data as a single desktop computer could process in 100 years.

“Through harnessing distributed computing power, DreamLab is helping to make personalised medicine a reality,” the researchers say.  “This project demonstrates how Imperial’s innovative research partnerships with corporate partners and members of the public are working together to tackle some of the biggest problems we face today, generating real societal impact.”…(More)”.

Artificial intelligence in non-profit organizations


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)”.