Can artificial intelligence wipe out bias unconscious bias from your workplace?

Curated on Posted on by Stefaan Verhulst

Lydia Dishman at Fast Company: “Unconscious bias is exactly what it sounds like: The associations we make whenever we face a decision are buried so deep (literally—the gland responsible for this, the amygdala, is surrounded by the brain’s gray matter) that we’re as unaware of them as we are of having to breathe.

So it’s not much of a surprise that Ilit Raz, cofounder and CEO of Joonko, a new application that acts as diversity “coach” powered by artificial intelligence, wasn’t even aware at first of the unconscious bias she was facing as a woman in the course of a normal workday. Raz’s experience coming to grips with that informs the way she and her cofounders designed Joonko to work.

The tool joins a crowded field of AI-driven solutions for the workplace, but most of what’s on the market is meant to root out bias in recruiting and hiring. Joonko, by contrast, is setting its sights on illuminating unconscious bias in the types of workplace experiences where few people even think to look for it….

so far, a lot of these resources have been focused on addressing the hiring process. An integral part of the problem, after all, is getting enough diverse candidates in the recruiting pipeline so they can be considered for jobs. Apps like Blendoor hide a candidate’s name, age, employment history, criminal background, and even their photo so employers can focus on qualifications. Interviewing.io’s platform even masks applicants’ voices. Text.io uses AI to parse communications in order to make job postings more gender-neutral. Unitive’s technology also focuses on hiring, with software designed to detect unconscious bias in Applicant Tracking Systems that read resumes and decide which ones to keep or scrap based on certain keywords.

But as Intel recently discovered, hiring diverse talent doesn’t always mean they’ll stick around. And while one 2014 estimate by Margaret Regan, head of the global diversity consultancy FutureWork Institute, found that 20% of large U.S. employers with diversity programs now provide unconscious-bias training—a number that could reach 50% by next year—that training doesn’t always work as intended. The reasons why vary, from companies putting programs on autopilot and expecting them to run themselves, to the simple fact that many employees who are trained ultimately forget what they learned a few days later.

Joonko doesn’t solve these problems. “We didn’t even start with recruiting,” Raz admits. “We started with task management.” She explains that when a company finally hires a diverse candidate, it needs to understand that the best way to retain them is to make sure they feel included and are given the same opportunities as everyone else. That’s where Joonko sees an opening…(More)”.

Data Maturity Framework

Curated on Posted on by Stefaan Verhulst

Center for Data Science and Public Policy: “Want to know if your organization is ready to start a data-driven social impact project? See where you are in our data maturity framework and how to improve your organizational, tech, and data readiness.

The Data Maturity Framework has three content areas:

  • Problem Definition
  • Data and Technology Readiness
  • Organizational Readiness

The Data Maturity Framework consists of:

  • A questionnaire and survey to assess readiness
  • Data and Technology Readiness Matrix
  • Organizational Readiness Matrix

The framework materials can be downloaded here, and you can complete our survey here. When we collect enough responses from enough organizations, we’ll launch an aggregate benchmarking report around the state of data in non-profits and government organizations. We ask that each problem be entered as a separate entry (rather than multiple problems from one organization entered in the same response).

We have adapted the Data Maturity Framework for specific projects:

Public services and the new age of data

Curated on Posted on by Stefaan Verhulst

 at Civil Service Quaterly: “Government holds massive amounts of data. The potential in that data for transforming the way government makes policy and delivers public services is equally huge. So, getting data right is the next phase of public service reform. And the UK Government has a strong foundation on which to build this future.

Public services have a long and proud relationship with data. In 1858, more than 50 years before the creation of the Cabinet Office, Florence Nightingale produced her famous ‘Diagram of the causes of mortality in the army in the east’ during the Crimean War. The modern era of statistics in government was born at the height of the Second World War with the creation of the Central Statistical Office in 1941.

How data can help

However, the huge advances we’ve seen in technology mean there are significant new opportunities to use data to improve public services. It can help us:

  • understand what works and what doesn’t, through data science techniques, so we can make better decisions: improving the way government works and saving money
  • change the way that citizens interact with government through new better digital services built on reliable data;.
  • boost the UK economy by opening and sharing better quality data, in a secure and sensitive way, to stimulate new data-based businesses
  • demonstrate a trustworthy approach to data, so citizens know more about the information held about them and how and why it’s being used

In 2011 the Government embarked upon a radical improvement in its digital capability with the creation of the Government Digital Service, and over the last few years we have seen a similar revolution begin on data. Although there is much more to do, in areas like open data, the UK is already seen as world-leading.

…But if government is going to seize this opportunity, it needs to make some changes in:

  • infrastructure – data is too often hard to find, hard to access, and hard to work with; so government is introducing developer-friendly open registers of trusted core data, such as countries and local authorities, and better tools to find and access personal data where appropriate through APIs for transformative digital services;
  • approach – we need the right policies in place to enable us to get the most out of data for citizens and ensure we’re acting appropriately; and the introduction of new legislation on data access will ensure government is doing the right thing – for example, through the data science code of ethics;
  • data science skills – those working in government need the skills to be confident with data; that means recruiting more data scientists, developing data science skills across government, and using those skills on transformative projects….(More)”.

Scientists have a word for studying the post-truth world: agnotology

Curated on Posted on by Stefaan Verhulst

 and  in The Conversation: “But scientists have another word for “post-truth”. You might have heard of epistemology, or the study of knowledge. This field helps define what we know and why we know it. On the flip side of this is agnotology, or the study of ignorance. Agnotology is not often discussed, because studying the absence of something — in this case knowledge — is incredibly difficult.

Doubt is our product

Agnotology is more than the study of what we don’t know; it’s also the study of why we are not supposed to know it. One of its more important aspects is revealing how people, usually powerful ones, use ignorance as a strategic tool to hide or divert attention from societal problems in which they have a vested interest.

A perfect example is the tobacco industry’s dissemination of reports that continuously questioned the link between smoking and cancer. As one tobacco employee famously stated, “Doubt is our product.”

In a similar way, conservative think tanks such as The Heartland Institute work to discredit the science behind human-caused climate change.

Despite the fact that 97% of scientists support the anthropogenic causes of climate change, hired “experts” have been able to populate talk shows, news programmes, and the op-ed pages to suggest a lack of credible data or established consensus, even with evidence to the contrary.

These institutes generate pseudo-academic reports to counter scientific results. In this way, they are responsible for promoting ignorance….

Under agnotology 2.0, truth becomes a moot point. It is the sensation that counts. Public media leaders create an impact with whichever arguments they can muster based in whatever fictional data they can create…Donald Trump entering the White House is the pinnacle of agnotology 2.0. Washington Post journalist Fareed Zakaria has argued that in politics, what matters is no longer the economy but identity; we would like to suggest that the problem runs deeper than that.

The issue is not whether we should search for identity, for fame, or for sensational opinions and entertainment. The overarching issue is the fallen status of our collective search for truth, in its many forms. It is no longer a positive attribute to seek out truth, determine biases, evaluate facts, or share knowledge.

Under agnotology 2.0, scientific thinking itself is under attack. In a post-fact and post-truth era, we could very well become post-science….(More)”.

How statistics lost their power – and why we should fear what comes next

Curated on Posted on by Stefaan Verhulst

 in The Guardian: “In theory, statistics should help settle arguments. They ought to provide stable reference points that everyone – no matter what their politics – can agree on. Yet in recent years, divergent levels of trust in statistics has become one of the key schisms that have opened up in western liberal democracies. Shortly before the November presidential election, a study in the US discovered that 68% of Trump supporters distrusted the economic data published by the federal government. In the UK, a research project by Cambridge University and YouGov looking at conspiracy theories discovered that 55% of the population believes that the government “is hiding the truth about the number of immigrants living here”.

Rather than diffusing controversy and polarisation, it seems as if statistics are actually stoking them. Antipathy to statistics has become one of the hallmarks of the populist right, with statisticians and economists chief among the various “experts” that were ostensibly rejected by voters in 2016. Not only are statistics viewed by many as untrustworthy, there appears to be something almost insulting or arrogant about them. Reducing social and economic issues to numerical aggregates and averages seems to violate some people’s sense of political decency.

Nowhere is this more vividly manifest than with immigration. The thinktank British Future has studied how best to win arguments in favour ofimmigration and multiculturalism. One of its main findings is that people often respond warmly to qualitative evidence, such as the stories of individual migrants and photographs of diverse communities. But statistics – especially regarding alleged benefits of migration to Britain’s economy – elicit quite the opposite reaction. People assume that the numbers are manipulated and dislike the elitism of resorting to quantitative evidence. Presented with official estimates of how many immigrants are in the country illegally, a common response is to scoff. Far from increasing support for immigration, British Future found, pointing to its positive effect on GDP can actually make people more hostile to it. GDP itself has come to seem like a Trojan horse for an elitist liberal agenda. Sensing this, politicians have now largely abandoned discussing immigration in economic terms.

All of this presents a serious challenge for liberal democracy. Put bluntly, the British government – its officials, experts, advisers and many of its politicians – does believe that immigration is on balance good for the economy. The British government did believe that Brexit was the wrong choice. The problem is that the government is now engaged in self-censorship, for fear of provoking people further.

This is an unwelcome dilemma. Either the state continues to make claims that it believes to be valid and is accused by sceptics of propaganda, or else, politicians and officials are confined to saying what feels plausible and intuitively true, but may ultimately be inaccurate. Either way, politics becomes mired in accusations of lies and cover-ups.

The declining authority of statistics – and the experts who analyse them – is at the heart of the crisis that has become known as “post-truth” politics. And in this uncertain new world, attitudes towards quantitative expertise have become increasingly divided. From one perspective, grounding politics in statistics is elitist, undemocratic and oblivious to people’s emotional investments in their community and nation. It is just one more way that privileged people in London, Washington DC or Brussels seek to impose their worldview on everybody else. From the opposite perspective, statistics are quite the opposite of elitist. They enable journalists, citizens and politicians to discuss society as a whole, not on the basis of anecdote, sentiment or prejudice, but in ways that can be validated. The alternative to quantitative expertise is less likely to be democracy than an unleashing of tabloid editors and demagogues to provide their own “truth” of what is going on across society.

Is there a way out of this polarisation? Must we simply choose between a politics of facts and one of emotions, or is there another way of looking at this situation?One way is to view statistics through the lens of their history. We need to try and see them for what they are: neither unquestionable truths nor elite conspiracies, but rather as tools designed to simplify the job of government, for better or worse. Viewed historically, we can see what a crucial role statistics have played in our understanding of nation states and their progress. This raises the alarming question of how – if at all – we will continue to have common ideas of society and collective progress, should statistics fall by the wayside….(More).”

DataCollaboratives.org – A New Resource on Creating Public Value by Exchanging Data

Curated on Posted on by Stefaan Verhulst

Recent years have seen exponential growth in the amount of data being generated and stored around the world. There is increasing recognition that this data can play a key role in solving some of the most difficult public problems we face.

However, much of the potentially useful data is currently privately held and not available for public insights. Data in the form of web clicks, social “likes,” geo location and online purchases are typically tightly controlled, usually by entities in the private sector. Companies today generate an ever-growing stream of information from our proliferating sensors and devices. Increasingly, they—and various other actors—are asking if there is a way to make this data available for the public good. There is an ongoing search for new models of corporate responsibility in the digital era around data toward the creation of “data collaboratives”.

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Today, the GovLab is excited to launch a new resource for Data Collaboratives (datacollaboratives.org). Data Collaboratives are an emerging form of public-private partnership in which participants from different sectors — including private companies, research institutions, and government agencies — exchange data to help solve public problems.

The resource results from different partnerships with UNICEF (focused on creating data collaboratives to improve children’s lives) and Omidyar Network (studying new ways to match (open) data demand and supply to increase impact).

Natalia Adler, a data, research and policy planning specialist and the UNICEF Data Collaboratives Project Lead notes, “At UNICEF, we’re dealing with the world’s most complex problems affecting children. Data Collaboratives offer an exciting opportunity to tap on previously inaccessible datasets and mobilize a wide range of data expertise to advance child rights around the world. It’s all about connecting the dots.”

To better understand the potential of these Collaboratives, the GovLab collected information on dozens of examples from across the world. These many and diverse initiatives clearly suggest the potential of Data Collaboratives to improve people’s lives when done responsibly. As Stefaan Verhulst, co-founder of the GovLab, puts it: “In the coming months and years, Data Collaboratives will be essential vehicles for harnessing the vast stores of privately held data toward the public good.”

In particular, our research to date suggests that Data Collaboratives offer a number of potential benefits, including enhanced:

  • Situational Awareness and Response: For example, Orbital Insights and the World Bank are using satellite imagery to measure and track poverty. This technology can, in some instances, “be more accurate than U.S. census data.”
  • Public Service Design and Delivery: Global mapping company, Esri, and Waze’s Connected Citizen’s program are using crowdsourced traffic information to help governments design better transportation.
  • Impact Assessment and Evaluation: Nielsen and the World Food Program (WFP) have been using data collected via mobile phone surveys to better monitor food insecurity in order to advise the WFP’s resource allocations….(More)

Popular Democracy: The Paradox of Participation

Curated on Posted on by Stefaan Verhulst

Book by Gianpaolo Baiocchi and Ernesto Ganuza: “Local participation is the new democratic imperative. In the United States, three-fourths of all cities have developed opportunities for citizen involvement in strategic planning. The World Bank has invested $85 billion over the last decade to support community participation worldwide. But even as these opportunities have become more popular, many contend that they have also become less connected to actual centers of power and the jurisdictions where issues relevant to communities are decided.

With this book, Gianpaolo Baiocchi and Ernesto Ganuza consider the opportunities and challenges of democratic participation. Examining how one mechanism of participation has traveled the world—with its inception in Porto Alegre, Brazil, and spread to Europe and North America—they show how participatory instruments have become more focused on the formation of public opinion and are far less attentive to, or able to influence, actual reform. Though the current impact and benefit of participatory forms of government is far more ambiguous than its advocates would suggest, Popular Democracy concludes with suggestions of how participation could better achieve its political ideals….(More)”

Harnessing the Power of Feedback Loops

Curated on Posted on by Stefaan Verhulst

Thomas Kalil and David Wilkinson at the White House: “When it comes to strengthening the public sector, the Federal Government looks for new ways to achieve better results for the people we serve. One promising tool that has gained momentum across numerous sectors in the last few years is the adoption of feedback loops.  Systematically collecting data and learning from client and customer insights can benefit organizations across all sectors.

The collection of these valuable insights—and acting on them—remains an underutilized tool.  The people who receive services are the experts on their effectiveness and usefulness.  While the private sector has used customer feedback to improve products and services, the government and nonprofit sectors have often lagged behind.  User experience is a critically important factor in driving positive outcomes.  Getting honest feedback from service recipients can help nonprofit service providers and agencies at all levels of government ensure their work effectively addresses the needs of the people they serve. It’s equally important to close the loop by letting those who provided feedback know that their input was put to good use.

In September, the White House Office of Social Innovation and the White House Office of Science and Technology Policy (OSTP) hosted a workshop at the White House on data-driven feedback loops for the social and public sectors.  The event brought together leaders across the philanthropy, nonprofit, and business sectors who discussed ways to collect and utilize feedback.

The program featured organizations in the nonprofit sector that use feedback to learn what works, what might not be working as well, and how to fix it. One organization, which offers comprehensive employment services to men and women with recent criminal convictions, explained that it has sought feedback from clients on its training program and learned that many people were struggling to find their work site locations and get to the sessions on time. The organization acted on this feedback, shifting their start times and providing maps and clearer directions to their participants.  These two simple changes increased both participation in and satisfaction with their program.

Another organization collected feedback to learn whether factory workers attend and understand trainings on fire evacuation procedures. By collecting and acting on this feedback in Brazil, the organization was able to help a factory reduce fire-drill evacuation time from twelve minutes to two minutes—a life-saving result of seeking feedback.

With results such as these in mind, the White House has emphasized the importance of evidence and data-driven solutions across the Federal Government.  …

USAID works to end extreme poverty in over 100 countries around the world. The Agency has recently changed its operational policy to enable programs to adapt to feedback from the communities in which they work. They did this by removing bureaucratic obstacles and encouraging more flexibility in their program design. For example, if a USAID-funded project designed to increase agricultural productivity is unexpectedly impacted by drought, the original plan may no longer be relevant or effective; the community may want drought-resistant crops instead.  The new, more flexible policy is intended to ensure that such programs can pivot if a community provides feedback that its needs have changed or projects are not succeeding…(More)”

Doctors take inspiration from online dating to build organ transplant AI

Curated on Posted on by Stefaan Verhulst

Ariel Bogle at Mashable :”When Bob Jones performed one of Victoria’s first liver transplants in 1988, he could not imagine that 29 years later he’d be talking about artificial intelligence and online dating. Jones is the director of Austin Health’s Victorian liver transplant unit in Melbourne, Australia, and along with his colleague Lawrence Lau, he has helped develop an algorithm that could potentially better match organ donors with organ recipients.

Comparing it to the metrics behind dating site eHarmony, Jone said they planned to use the specially-designed AI to improve the accuracy of matching liver donors and recipients, hopefully resulting in less graft failures and fewer patient deaths.

“It’s a specially designed machine learning algorithm using multiple donor and recipient features to predict the outcome,” he explained.

The team plugged around 25 characteristics of donors and recipients into their AI, using the data points to retrospectively predict what would happen to organ grafts.

“We used all the basic things like sex, age, underlying disease, blood type,” he said. “And then there are certain characteristics about the donor … and all the parameters that might indicate the liver might be upset.”

Using the AI to assess the retrospective results of 75 adult patients who’d had transplants, they found the method predicted graft failure 30 days post-transplant at an accuracy of 84 percent compared to 68 percent with current methods.

“It really meant for the first time we could assess an organ’s suitability in a quantitive way,” he added, “as opposed to the current method, which really comes down to the position of the doctor eyeballing all the data and making a call based on their experience.”

Improving the accuracy of organ donor matches is vital, because as Jones put it, “it’s an extraordinary, precious gift from one Australian to another.”…(More)”

How Mobile Crowdsourcing Can Improve Occupational Safety

Curated on Posted on by Stefaan Verhulst

Batu Sayici & Beth Simone Noveck at The GovLab’s Medium: “With 150 workers dying each day from hazardous working conditions, work safety continues to be a serious problem in the U.S. Using mobile technology to collect information about workplace safety conditions from those on the ground could help prevent serious injuries and save lives by accelerating the ability to spot unsafe conditions. The convergence of wireless devices, low-cost sensors, big data, and crowdsourcing can transform the way we assess risk in our workplaces. Government agencies, labor unions, workers’ rights organizations, contractors and crowdsourcing technology providers should work together to create new tools and frameworks in a way that can improve safety and provide value to all stakeholders.

Crowdsourcing (the act of soliciting help from a distributed audience) can provide a real-time source of data to complement data collected by government agencies as part of the regulatory processes of monitoring workplace safety. Having access to this data could help government agencies to more effectively monitor safety-related legal compliance, help building owners, construction companies and procurement entities to more easily identify “responsible contractors and subcontractors,” and aid workers and unions in making more informed choices and becoming better advocates for their own protection. Just as the FitBit and Nike Wristband provide individuals with a real-time reflection of their habits designed to create the incentive for healthier living, crowdsourcing safety data has the potential to provide employers and employees alike with a more accurate picture of conditions and accelerate the time needed to take action….(More)”