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THE LACK OF diversity at tech companies is well-established: Less than 10 percent of workers at Google and LinkedIn are non-Asian minorities, for example, and only 31 percent of employees at Google are women. But the technology industry is guilty of another serious blunder that hasn’t spurred the same volume of national conversation: a lack of interest, and failure to invest, in the capacity of small and mid-sized cities to shape technology’s evolution.

Many of the best-known tech companies were launched and remain headquartered in Silicon Valley, a region that’s home to 3 million people. Tomorrow’s tech ideas are also being tested in larger cities: witness AmazonFresh Pickup(Seattle) and Uber’s autonomous vehicle trials (San Francisco, Pittsburgh, and Tempe, Arizona); although smart city initiatives are taking off in smaller cities, the larger cities still have more than their share of smart city projects, not to mention the media coverage that perpetuates larger cities’ market advantage.

But beta-testing new technologies and products in smaller cities could benefit communities across the US. After all, the success of Massachusetts’ universal healthcare plan served as the blueprint for the (now imperiled) Affordable Care Act. And as with universal health care, small and mid-sized cities can be incubators for tech policy, allowing lawmakers to test programs on a small scale before taking them nationwide.

It’s true for companies as well as governments: Startups can implement and market concepts to a city of 100,000 much faster and more cheaply than to cities with 1 million residents. What’s more, smaller cities’ lower housing costs and, often, taxes allow tech companies to set up shop less expensively. The citizens of these cities bring diverse points of view to the tech conversation, just as minorities and women do, and their outlooks can improve tech planning and products.

I used to think that bringing the broad technological innovations common in large metropolitan areas to smaller cities was impractical, given the disparities in cultures, populations, budgets, and infrastructure.

But three experiences changed my mind. First, learning from one of the leading minds in tech policy, Susan Crawford, who showed me that data-driven policy could and should be leveraged to help all cities. Second, lobbying leaders and citizens in my hometown of Shreveport, Louisiana, to pursue city-wide broadband access and founding a tech company that focuses on marketing black- and Latino/a-owned businesses. Third, discovering that smaller cities have legitimate price, scale, and knowhow barriers, but many of these obstacles have been broken down by a proliferation of tools that are affordable, scalable, and user-friendly.

Still, smaller cities struggle to compete against big cities in attracting resources or private enterprise. They sometimes cannot afford grant writers or lobbyists, and they must rely on a smaller base of innovative and strategic thinkers. By contrast, cities like Chicago and Los Angeles have armies of grant writers and need only spend a fraction of each tax dollar to funnel millions to lobbyists at the state and federal level.

While technological investments in big cities can seem financially insignificant, the same ventures in smaller cities have the potential to radically transform their citizens’ quality of life. After Chattanooga, Tennessee installed its own broadband network, for example, its unemployment rate fell from 7.8 percent to 4.1 percent, and wages climbed to the third highest of all mid-sized US cities.

When smaller cities invest in smart technology projects, they profit in the long run by optimizing their use of resources and delivering services more efficiently. Inspired by the millions that Louisville, Kentucky’s Office of Performance Improvement saved by optimizing its use of data, I recently pitched the benefits of data collection and a city-owned broadband network to the mayor and city council in Shreveport, Louisiana. While my proposal has been well-received, funding is not ensured. Budget constraints force many smaller localities to choose between fixing potholes and investing in long-term tech initiatives. And without investment from outside sources, the potholes usually win.

Tech-based grants that focus on smaller cities, such as the Knight Foundation’s Community Foundations Program or Bloomberg’s What Works Cities, can help with the funding challenges. Currently 78 percent of venture capital is given to only three states: California, New York, and Massachusetts. The Obama administration announced $80 million of funding for local governments. If President Trump’s promised trillion-dollar infrastructure plan passes, hopefully some of that funding can help smaller cities pursue projects at the intersection of infrastructure and smart city tech.

As an African-American law student studying innovation, I wish speakers who looked like me visited my classes to talk about technology. And I’ve felt similarly isolated when reading thousands of pages about innovative cities that do not look like my hometown. Various forces in the tech world are denying minorities and smaller cities the chance to influence the direction of technology’s march into the future. Just as minorities deserve equal opportunities in the tech world, Shreveport and other cities like it need technology just as much as New York and San Francisco.

Credit: Adrian Perkins @ Wired.com

4 Tips on Getting Ahead of Employee Burnout

It’s no secret that work can be stressful, but it doesn’t make it easier to face the fact that burnout is the cause for half of workplace turnover each year. In such a working environment, it’s imperative for companies to understand how to keep their employees happy, satisfied and productive to fight this type of mass exodus.

Sometimes there are inevitable workplace obstacles that deter employees even when they find themselves in a job they love and are passionate about. We need to overcome these obstacles even if it seems like a daunting task. It can start simply. Between overbearing bosses, office conflict and even outdated workplace technology, there are a number of factors that employers can and must keep track of to gauge the overall happiness and, in turn, boost retention in their offices.

In search for an answer, Teem recently released its second annual 2017 Employee Happiness Index, benchmarking the key factors that keep employees showing up for work every day — and those that drive them away. Here’s what we’ve learned and how we can use these learnings to keep employees fulfilled and engaged.

Don’t forget the people.

As Neil Diamond has sung, “Money talks, but it can’t sing and dance and it can’t walk” — but you know who does? People. The reason 48 percent of employees are somewhat happy or unhappy is because they feel underappreciated or a lack of work-life balance. Although money does hold high influence, people are social creatures requiring camaraderie and a sense of belonging. For the workforce, liking the people they work with is one of the top factors leading to employee happiness, outranking both a good standing with management and a collaborative work environment as the top motivator. But keep in mind, it’s not about creating groups of best friends. It’s about espousing an environment that fosters mutual respect and trust.

This may be difficult with the increased presence of new technology in the workplace that can often eliminate interpersonal activities that lead to this sense of belonging. With all the discussion about AI and the future of work, sometimes the importance of good peer-to-peer interactions gets lost for sake of technologically-driven “efficiency” and “productivity.” But the effort can’t be lopsided. We still need productive human teams behind the machines.

Automate me.

In light of the technological takeover, the proverbial questions in the workplace have now become: What technology can we introduce to boost efficiency? How will this affect our workforce? While quality camaraderie with coworkers is important to fostering happiness and loyalty, it’s not to say organizations can or should eschew new technologies. Let’s face it, who doesn’t want tools that make life easier?

Tech automation, like AI and machine learning, has the ability to augment workflows, increase efficiency and absorb mundane tasks. It’s no wonder why 41 percent of respondents are excited about AI making their jobs easier rather than concerning themselves with AI eliminating it. Organisations need to ensure the right technology is there to make their workforce’s life easier, but can’t forget to do it in a measured way that affords comfort (not a fear of displacement) to the employee.

Avoid the battle for space.

Employees report to spending a third (34 percent) of their days in meetings which is eating up valuable time and causing a time crunch for day-to-day tasks. The anxiety this generates is amplified by constant congestion and competition for shared work spaces like conference rooms, huddle rooms, phone banks, etc. Rushed and anxious employees faced with poorly managed spaces and tools can make for an extremely dissatisfied team. And if the situation gets mismanaged, the resentments that stem from it can lead to conflicts at work and have to be cited as a major cause for disagreement and discomfort at work.

Employers should ensure that respect and professionalism are maintained. In this case, employers should do their best to make certain that spaces and tools are used appropriately and available for those that need it most to be successful. It can be done with something as simple as tools that make it clear when meetings should start and finish.

Tune in, turn on = burnt out.

This is a no brainer. Unless it is an emergency, employees should never be or feel forced to be plugged in 24/7. Our Index found that one of the few things all generations surveyed agreed on was that their least favorite aspect of the modern workplace is feeling that they are always on. HR policies can go a long way to counter this feeling.

For instance, HR policies that draw a line on client communication. Employees are sure to be happier when clients cannot text or IM them late into the evenings or on weekends. Building on this train of thought, time off should also be treated as time off. Organizations should do their best to leave employees alone during PTO and vacation; no one wants to feel nagged outside of the office. Emergencies will happen and there will be times where rules like these will have to be overruled, but employees will be much more likely to jump on board knowing that if it wasn’t critical, they wouldn’t be contacted.

Ultimately, it all comes down to the idea of balance. New tools and technology are making it easier to work, but are simultaneously introducing barriers to work. The result is work environments with a high churn rate, as employee move on to seemingly greener pastures. Remember, organizations don’t need to implement all the tools or have an “always-on” team. What they do need is happy workforce in a space that is bolstered by streamlined workflows. Are you offering what your employees need to keep ‘em coming back?

Credit: Zach Holmquist @ Entrepeneur


BY NOW MOST of us have learned first-hand that human-AI relations need some work. Amazon’s Alexa personal assistant is plugged into one of the world’s largest online stores and can pull information from Wikipedia. But can it help you when you yell out what in the moment feels like a simple request to play that summer banger you just heard, starting at the catchy chorus? “I’m sorry, I don’t understand the question.”

All supposedly smart helpers including Apple’s Siri and Google’s prosaically named Google Assistant are capable of frustrating feats of what can feel like artificial stupidity. It’s one reason that Google is starting a new research push to understand and improve the relations between humans and AI. PAIR, for People + AI Research initiative, was announced today and will be led by two experts in data visualization, Fernanda Viégas and Martin Wattenberg. One thing they hope to do is create a toolkit of techniques and ideas about how to design AI systems less prone to disappointing or surprising us humans.

Virtual assistants get infuriating when they fail to do something we expect to be within their capabilities. Viégas says that she’s interested in studying how people form expectations about what such systems can and can’t do—and how virtual assistants themselves might be designed to nudge us toward only asking things that won’t lead to disappointment. “One of the research questions is how do you reset a user’s expectations on the fly when they’re interacting with a virtual assistant,” she says.

Viégas and Wattenberg will lead PAIR out of Google’s Mountain View-based Google Brain AI research group, where they previously worked mostly on developing tools to let researchers and engineers peek inside the workings of machine learning systems. PAIR will see them keep working on that, and the project today released two open source tools that help engineers understand the data they’re feeding into machine learning systems. But the new initiative will also work on making artificial intelligence more transparent to people not expert in the technology.

The deep learning algorithms that have lately proved so useful for analyzing our personal data or diagnosing diseases from medical imaging also have a reputation for being what researchers dub “black boxes”, meaning it can be difficult to see why a system spat out a particular decision, such as a diagnosis.

That’s a problem as such software gets closer to being used in life-or-death situations in the clinic or on our roads inside autonomous vehicles. “The doctor needs to have some sense of what’s happening and why they got a recommendation or prediction,” Viégas says. That might mean creating ways for diagnostic software to highlight the pieces of a scan that influenced its recommendation or having it write explanations in text.

Google’s project comes at a time of increasing attention on the human consequences of of AI. Today the Ethics and Governance of Artificial Intelligence Fund, with backers including the Knight Foundation and LinkedIn cofounder Reid Hoffman, announced $7.6 million in grants to civil society organizations to study the changes AI might cause in areas such as labor markets and criminal justice systems.

Like those new projects, Google says much of PAIR’s work will take place out in the open. MIT and Harvard professors Hal Abelson and Brendan Meade will collaborate with PAIR on how AI can enhance education and science, for example. But working on making humans and AI more compatible also has clear business benefits for what CEO Sundar Pichai describes as an “AI first” company.

If PAIR can help AI integrate more smoothly into industries like healthcare it could help bring new customers to Google’s AI-centric cloud business, for example. Viégas says she also wants to work closely with Google’s product teams, such as the one behind the Google assistant. Such a collaboration could be lucrative if it results in keeping people more engaged with the product, which acts as a gateway to the company’s broader services and underlying ad business. PAIR has a shot at not only helping advance society’s understanding of what happens when humans and AI collide, but boosting Google’s bottom line.

Credit to Tom Simonite @ Wired


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