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Startups net more than capital with NBA players as investors

Posted by on Jun 1, 2019 in Alexa, Andre Iguodala, Basketball, Carmelo Anthony, Column, Dan Porter, david stern, Facebook, Golden State Warriors, Google, Kevin Durant, Messenger, national basketball association, NBA, overtime, player, SMS, Snap, Snapchat, snaptravel, Social Media, Spark Capital, Startups, stephen curry, TC, Telstra Ventures, toronto, twitch | 0 comments

If you’re a big basketball fan like me, you’ll be glued to the TV watching the Golden State Warriors take on the Toronto Raptors in the NBA finals. (You might be surprised who I’m rooting for.)

In honor of the big games, we took a shot at breaking down investment activities of the players off the court. Last fall, we did a story highlighting some of the sport’s more prolific investors. In this piece, we’ll take a deeper dive into just what having an NBA player as a backer can do for a startup beyond the capital involved. But first, here’s a chart of some startups funded by NBA players, both former and current.

 

In February, we covered how digital sports media startup Overtime had raised $23 million in a Series B round of funding led by Spark Capital. Former NBA Commissioner David Stern was an early investor and advisor in the company (putting money in the company’s seed round). Golden State Warriors player Kevin Durant invested as part of the company’s Series A in early 2018 via his busy investment vehicle, Thirty Five Ventures. And then, Carmelo Anthony invested (via his Melo7 Tech II fund) earlier this year. Other NBA-related investors include Baron DavisAndre Iguodala and Victor Oladipo, and other non-NBA backers include Andreessen Horowitz and Greycroft.

I talked to Overtime’s CEO, 27-year-old Zack Weiner, about how the involvement of so many NBA players came about. I also wondered what they brought to the table beyond their cash. But before we get there, let me explain a little more about what Overtime does.

Founded in late 2016 by Dan Porter and Weiner, the Brooklyn company has raised a total of $35.3 million. The pair founded the company after observing “how larger, legacy media companies, such as ESPN, were struggling” with attracting the younger viewer who was tuning into the TV less and less “and consuming sports in a fundamentally different way.”

So they created Overtime, which features about 25 to 30 sports-related shows across several platforms (which include YouTube, Snapchat, Instagram, Facebook, TikTok, Twitter and Twitch) aimed at millennials and the Gen Z generation. Weiner estimates the company’s programs get more than 600 million video views every month.

In terms of attracting NBA investors, Weiner told me each situation was a little different, but with one common theme: “All of them were fans of Overtime before we even met them…They saw what we were doing as the new wave of sports media and wanted to get involved. We didn’t have to have 10 meetings for them to understand what we were doing. This is the world they live and breathe.”

So how is having NBA players as investors helping the company grow? Well, for one, they can open a lot of doors, noted Weiner.

“NBA players are very powerful people and investors,” he said. “They’ve helped us make connections in music, fashion and all things tangential to sports. Some have created content with us.”

In addition, their social clout has helped with exposure. Their posting or commenting on Instagram gives the company credibility, Weiner said.

“Also just, in general, getting their perspectives and opinions,” he added. “A lot of our content is based on working with athletes, so they understand what athletes want and are interested in being a part of.”

It’s not just sports-related startups that are attracting the interest of NBA players. I also talked with Hussein Fazal, the CEO of SnapTravel, which recently closed a $21.2 million Series A that included participation from Telstra Ventures and Golden State Warriors point guard Stephen Curry.

Founded in 2016, Toronto-based SnapTravel offers online hotel booking services over SMS, Facebook Messenger, Alexa, Google Home and Slack. It’s driven more than $100 million in sales, according to Fazal, and is seeing its revenue grow about 35% quarter over quarter.

Like Weiner, Fazal told me that Curry’s being active on social media about SnapTravel helped draw positive attention and “add a lot of legitimacy” to his company.

“If you’re an end-consumer about to spend $1,000 on a hotel booking, you might be a little hesitant about trusting a newer brand like ours,” he said. “But if they go to our home page and see our investors, that holds some weight in the eyes of the public, and helps show we’re not a fly-by-night company.”

Another way Curry’s involvement has helped SnapTravel is in terms of the recruitment and retainment of employees. Curry once spent hours at the office, meeting with employees and doing a Q&A.

“It was really cool,” Fazal said. “And it helps us stand out from other startups when hiring.”

Regardless of who wins the series, it’s clear that startups with NBA investors on their team have a competitive advantage. (Still, Go Raptors!)


Source: The Tech Crunch

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Reality Check: The marvel of computer vision technology in today’s camera-based AR systems

Posted by on May 15, 2019 in Animation, AR, ar/vr, Artificial Intelligence, Augmented Reality, Column, Computer Vision, computing, Developer, digital media, Gaming, gif, Global Positioning System, gps, mobile phones, neural network, starbucks, TC, virtual reality, VR | 0 comments

British science fiction writer, Sir Arther C. Clark, once said, “Any sufficiently advanced technology is indistinguishable from magic.”

Augmented reality has the potential to instill awe and wonder in us just as magic would. For the very first time in the history of computing, we now have the ability to blur the line between the physical world and the virtual world. AR promises to bring forth the dawn of a new creative economy, where digital media can be brought to life and given the ability to interact with the real world.

AR experiences can seem magical but what exactly is happening behind the curtain? To answer this, we must look at the three basic foundations of a camera-based AR system like our smartphone.

  1. How do computers know where it is in the world? (Localization + Mapping)
  2. How do computers understand what the world looks like? (Geometry)
  3. How do computers understand the world as we do? (Semantics)

Part 1: How do computers know where it is in the world? (Localization)

Mars Rover Curiosity taking a selfie on Mars. Source: https://www.nasa.gov/jpl/msl/pia19808/looking-up-at-mars-rover-curiosity-in-buckskin-selfie/

When NASA scientists put the rover onto Mars, they needed a way for the robot to navigate itself on a different planet without the use of a global positioning system (GPS). They came up with a technique called Visual Inertial Odometry (VIO) to track the rover’s movement over time without GPS. This is the same technique that our smartphones use to track their spatial position and orientation.

A VIO system is made out of two parts.


Source: The Tech Crunch

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As a founder, I mistook my work for self-worth

Posted by on May 11, 2019 in Column, Health, mental health, Startups, uncollege | 0 comments

These days, most days are good days. My clients are founder and executives, I set my own schedule, and I live in a city I love. As an executive coach and advisor, I work with founders and CEOs of companies who have raised more than $100M. Like any enterprise, it’s taken a lot of building, planning, and failing for me to get where I am.

What I’m supposed to tell you is that I worked hard and persevered – and I did.

But what I’m not supposed to tell you is how it felt to do all that failing, and above all how, for years, shame was the primary emotion that guided my life and career. How, at my lowest point, I felt worthless. How I even contemplated self-harm.

It takes a herculean energy to start a company, which is maybe why, so often, our stories sound like myths. Mine went something like this: If I could just raise money from a top-tier VC, get to $1M in revenue, and sell the business for more than $5M, then I’d be good enough. I’d be the successful young adult I wanted to be. Then, once I had made my first million, I could take a swing and start a billion-dollar company.

The fact that I didn’t feel worthy of love, that I lacked inherent value, drove my decisions. My failure to reach the goals I set reinforced the belief I that I was unworthy. Luckily, I eventually found the self-awareness to realize that blindly pursuing goals I couldn’t achieve was unhealthy.

But I didn’t expect that walking away from my job as CEO would break me, nor did I realize how far I would sink.

I thought that if I was “successful,” people would see that I wasn’t flawed, and I’d finally be worth something.

After extensive therapy, it’s easy for me to see how misguided I was from the outset. Shame, most of the time, is a thing of the past. But for a long time, it fueled every decision I made yet never seemed to exhaust itself – there was always more. In the business world, this is more common than we’re led to think — almost every entrepreneur I meet shares an experience “otherness.” We glorify failure, but we don’t have the patience to honor the pain that turns into the shame of feeling “I’m not good enough.”

We are supposed to be resolute, driven, and resilient. To that end, I want to share what I’ve learned so others who struggle with worthlessness know they aren’t alone, and that happiness – and enjoying success – is still possible.

Accidentally Starting a Company

At 19, I didn’t have a grand plan to change higher education. I was simply a pissed off freshman in college. In an interview with the Chronicle of Higher Education, Jeff Young asked me: what would I do with UnCollege, the site I’d just put online?

UnCollege was a fledgling website I’d created out of my frustration in college. It was designed to create a community of people who were frustrated with the status quo in higher education. In that pivotal moment, when Young asked about my plans for the site, I immediately tied my self-worth to its future. It was, after all, the reason I was being interviewed by a major publication. I had to turn UnCollege into something, or else I’d be a failure – and worse, everyone would know it, because now it was public.

From then on, I started a mental list of what I needed to do to be a successful entrepreneur. My list grew quickly and each item carried a familiar caveat. I must write a book or I’m worthless. I must start a company and raise $1M or I’m worthless I must speak at conferences around the world or I’m worthless.

I did raise money. I did start the company. I got to $1M in revenue. Each time I checked one of these boxes, I wasn’t happier. I started to be afraid I would never feel I was enough. I didn’t feel “successful,” especially in the way I saw success portrayed by others, both online and in the industry.

I thought that if I was “successful,” people would see that I wasn’t flawed, and I’d finally be worth something. What I didn’t know is that each time I checked something off my mental checklist, I’d be consumed with shame and insecurity, needing to check the next item off the list in order to feel worthy.

Instead, I felt trapped. I didn’t yet know that self-worth must come from within.

Mistaking my work for self-worth

I realized quickly that I’d committed myself to starting a company because I was afraid of failure, not because I had carefully considered what problem I wanted to dedicate the next ten years of my life to solving. Nonetheless, UnCollege enrolled its first students in September 2013.

That fall, I began to suspect I’d made a mistake. But I was afraid to tell my investors, and those that had supported me to get the business this far. My survival skill was to smile and act like I knew better than everyone else. If only I’d had the courage to sincerely ask for advice.

One consequence of not asking for help was I had to let go of two of the first people I hired, and layoff two more because we didn’t have the cash.

The first cohort was a disaster. I hadn’t designed a properly structured curriculum, and students were dissatisfied. The students liked the community of self-directed learners, but the company wasn’t delivering value beyond the community. Two weeks before the end of the semester, the students declared mutiny and demanded to know what we were going to do to improve the program.

I was terrified and wanted to leave, but we’d already taken money for the next cohort of students. I believed I didn’t have any other choice. We created a coaching program, hired coaches, built two dozen new workshops, and started working to get students placed into internships. The coaching model we built worked, and we spent the next two years improving it.

In the spring of 2015, I called my lead investor, my voice shaking. He knew that I had my share of fear and insecurity, but I told him clearly that day “I can’t do this anymore. It’s going to break me.”

Ignoring my feelings was a survival skill as child. Ignoring the doubt and anxiety caused by early critics allowed me to push through and launch a company. But it was also my achilles heel.

At the same time I was experiencing burnout, the company was pivoting from a college alternative into a pre-college program. The board agreed: it was time to hire a CEO.

After hiring a CEO, it became more difficult to motivate myself to go to work every day. Getting out of bed became a chore. One morning, after a breakfast with a prospective investor at the Four Seasons, I sat down on a bench outside and began to cry. Looking up, I saw one of our previous students waving at me, and quickly wipe away my tears to give him a faint smile.

I felt embarrassed, weak, and helpless.

Deriving identity from my work wasn’t working, and I knew I had to put an end to it. But what were my alternatives?

I was excited for my company and its new leadership, but I was anxious. I was empty. I didn’t know where the company stopped and I began. At my 25th birthday dinner, I couldn’t eat. I was consumed by shame, by fear. I managed to hold off all through dinner, but as soon as I arrived home I broke down sobbing.

Shame is a Habit

In December, I was no longer CEO of my own company. Six months later, I couldn’t get out of bed.

Those first few months I spent catching my breath. I was still on the board of the company, but I didn’t control it. As I began constructing a life post-UnCollege, I had no idea where to start. I didn’t yet realize it, but I needed to go through the individuation process – to figure out who I was and what I believed, independent of my family of origin. Already 25, I’d managed to avoid these questions. The irony is not lost on me that most of my peers faced them in college.

Shame is a consumptive state of being. The longer I went without answers to questions tied to my selfhood, the more shame ate me up. What did I care about? Did I make the right choice? Was the sacrifice I’d made to start this company worth it? Had I taken the wrong path? Was all the pain I’d been through a waste? Would I ever learn to feel happy again? I was beginning to feel as if I had no self at all.

Without a job to make me feel useful, I spent most days drinking at Dolores Park in San Francisco. I knew this wasn’t healthy, but I convinced myself I deserved it after years of hard work. Again, I was only 25. Life had lost its color. Things that once brought me joy no longer did. I could no longer grin and bear the pain. Believing my own bullshit about how I was going to be OK was no longer working. The more this cycle continued, the stronger it got, and the weaker I felt – all the more trapped.

Even the most successful people carry trauma, and often lash themselves onward with its whip

One Monday in October, I found myself completely unable to function. Alone in my house, I realized I hadn’t gotten out of bed or eaten a meal for several days. I was supposed to get on a plane to fly to Minneapolis, and I just couldn’t bring myself to do it. Instead, I called my dad, who encouraged me to message my doctor and say, “I think I might be depressed.” I was still too scared to pick up the phone, and it would be another few months before I uttered those words out loud. I started therapy, but things got worse before they got better.

Beyond “I’m sad that my company didn’t turn into what I wanted,” I didn’t have names for my emotions. A lightbulb moment came when my therapist asked, “When have you felt anxiety?” The only example I could think of was the time my company was only a few days from running out of cash.

“Have you ever considered that you only feel your emotions at extremes – a 20, for example, on a 1-10 scale? It’s human to feel anxiety in day-to-day life.”

That opened a door. I wasn’t just sad about leaving my company: I felt shame that I wasn’t “successful.” It wasn’t only my identity I’d tied to the business, but my self-worth. Deep down, my core belief that I – myself – wasn’t good enough. This is shame by definition: a hole that forms in our deepest selves we can never fill because it seems permanent; it seems, by nature, that this is who we are, not what we have done.

Shame often comes from feeling different as a child. In my case, I stuttered as a child. My voice was too ugly to be heard, so I concealed it. I used synonyms to avoid the sounds I couldn’t make. I did this because I couldn’t handle the intense shame of not being able to say my own last name without stuttering. In doing so, I learned to ignore, to numb those intense feelings of shame. I coped, and because I learned to cope so early in life, I learned to numb the rest of my feelings along with it.

By the time I launched a company, all those feelings that tell us “something’s wrong” – sadness, exhaustion, frustration, embarrassment, anxiety, guilt, and so on – were so buried and so unnamed that I could only tell myself “You are what’s wrong” when I hit a block, when I encountered the normal and natural failures that entrepreneurs face every day, no matter how successful in the long run.

Ignoring my feelings was a survival skill as child. Ignoring the doubt and anxiety caused by early critics allowed me to push through and launch a company. But it was also my achilles heel. It led me to derive my identity and self-worth from my work.

A CEO, the story goes, has it all together: a CEO is a visionary who sees around corners without any help. Because of this, I couldn’t give myself permission to ask for help, and when I left the company, I lacked the vocabulary or awareness to describe my feelings. My perfectionism, which long ago enabled me to ignore my stuttering, had associated help with failure, and failure with shame.

All these years later, I still couldn’t allow myself to ask for help.

Learning to tame trauma

Stress, overwhelm, burnout: these were the closest words I had to describe my feelings. This is startup lingo for things you cycle through now and again, and the story goes that we push past them and keep working. But these aren’t emotions. They are coverups for feelings of pain and shame. Ultimately, they describe trauma.

When most people think of trauma they imagine a car crash, or maybe a natural disaster or physical assault. An event that curtails your ability to function entirely. But trauma is simply a piece of the past we carry with us in the present that shapes us — in both positive and negative ways.

In my coaching career, I’ve worked with entrepreneurs and executives who felt too pretty, too ugly, too gay, too fat, too foreign, too dumb, too smart, too dark, or too light. These were the holes of shame they couldn’t fill and believed would always be there. They weren’t by any means failures: even the most successful people carry trauma, and often lash themselves onward with its whip. But shame is something even the best of us can’t outrun. Eventually it catches up with you. It took me years to understand this, and being compassionate towards myself will be a lifelong journey.

Once I had the vocabulary to separate my self-worth from my professional ambitions, UnCollege was a failure I could be proud of, not to mention a learning experience I could bring to my next project: Helping others learn to love themselves, and as a result, build wildly successful companies.


Source: The Tech Crunch

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Three ‘new rules’ worth considering for the internet

Posted by on May 9, 2019 in Column, Internet of things, internet security, Mark Zuckerberg, Opinion, regulations | 0 comments

In a recent commentary, Facebook’s Mark Zuckerberg argues for new internet regulation starting in four areas: harmful content, election integrity, privacy and data portability. He also advocates that government and regulators “need a more active role” in this process. This call to action should be welcome news as the importance of the internet to nearly all aspects of people’s daily lives seems indisputable. However, Zuckerberg’s new rules could be expanded, as part of the follow-on discussion he calls for, to include several other necessary areas: security-by-design, net worthiness and updated internet business models.

Security-by-design should be an equal priority with functionality for network connected devices, systems and services which comprise the Internet of Things (IoT). One estimate suggests that the number of connected devices will reach 125 billion by 2030, and will increase 50% annually in the next 15 years. Each component on the IoT represents a possible insecurity and point of entry into the system. The Department of Homeland Security has developed strategic principles for securing the IoT. The first principle is to “incorporate security at the design phase.” This seems highly prudent and very timely, given the anticipated growth of the internet.

Ensuring net worthiness — that is, that our internet systems meet appropriate and up to date standards — seems another essential issue, one that might be addressed under Zuckerberg’s call for enhanced privacy. Today’s internet is a hodge-podge of different generations of digital equipment, unclear standards for what constitutes internet privacy and growing awareness of the likely scenarios that could threaten networks and user’s personal information.

Recent cyber incidents and concerns have illustrated these shortfalls. One need only look at the Office of Personnel Management (OPM) hack that exposed the private information of more than 22 million government civilian employees to see how older methods for storing information, lack of network monitoring tools and insecure network credentials resulted in a massive data theft. Many networks, including some supporting government systems and hospitals, are still running Windows XP software from the early 2000s. One estimate is that 5.5% of the 1.5 billion devices running Microsoft Windows are running XP, which is now “well past its end-of-life.” In 2016, a distributed denial of service attack against the web security firm Dyn exposed critical vulnerabilities in the IoT that may also need to be addressed.

Updated business models may also be required to address internet vulnerabilities. The internet has its roots as an information-sharing platform. Over time, a vast array of information and services have been made available to internet users through companies such as Twitter, Google and Facebook. And these services have been made available for modest and, in some cases, no cost to the user.

Regulation is necessary, but normally occurs only once potential for harm becomes apparent.

This means that these companies are expending their own resources to collect data and make it available to users. To defray the costs and turn a profit, the companies have taken to selling advertisements and user information. In turn, this means that private information is being shared with third parties.

As the future of the internet unfolds, it might be worth considering what people would be willing to pay for access to traffic cameras to aid commutes, social media information concerning friends or upcoming events, streaming video entertainment and unlimited data on demand. In fact, the data that is available to users has likely been compiled using a mix of publicly available and private data. Failure to revise the current business model will likely only encourage more of the same concerns with internet security and privacy issues. Finding new business models — perhaps even a fee-for-service for some high-end services — that would support a vibrant internet, while allowing companies to be profitable, could be a worthy goal.

Finally, Zuckerberg’s call for government and regulators to have a more active role is imperative, but likely will continue to be a challenge. As seen in attempts at regulating technologies such as transportation safety, offshore oil drilling and drones, such regulation is necessary, but normally occurs only once potential for harm becomes apparent. The recent accidents involving the Boeing 737 Max 8 aircraft could be seen as one example of the importance of such government regulation and oversight.

Zuckerberg’s call to action suggests a pathway to move toward a new and improved internet. Of course, as Zuckerberg also highlights, his four areas would only be a start, and a broader discussion should be had as well. Incorporating security-by-design, net worthiness and updated business models could be part of this follow-on discussion.


Source: The Tech Crunch

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Amazon’s one-two punch: How traditional retailers can fight back

Posted by on Apr 18, 2019 in 6 River Systems, Amazon, Artificial Intelligence, Column, E-Commerce, eCommerce, getvu, IBM, jeff bezos, Kiva Systems, locus robotics, magazino, merchandising, online retail, online shopping, physical retail, Retail, retailers, siemens, TC, whole foods | 0 comments

If you think physical retail is dead, you couldn’t be more wrong. Despite the explosion in e-commerce, we’re still buying plenty of stuff in offline stores. In 2017, U.S. retail sales totaled $3.49 trillion, of which only 13 percent (about $435 billion) were e-commerce sales. True, e-commerce is growing at a much faster annual pace. But we’re still very far from the tipping point.

Amazon, the e-commerce giant, is playing an even longer game than everyone thinks. The company already dominates online retail — Amazon accounted for almost 50 percent of all U.S. e-commerce dollars spent in 2018. But now Amazon is eyeing the much bigger prize: modernizing and dominating retail sales in physical locations, mainly through the use of sophisticated data analysis. The recent reports of Amazon launching its own chain of grocery stores in several U.S. cities — separate from its recent Whole Foods acquisition — is just one example of how this could play out.

You can think of this as the Amazon one-two punch: The company’s vast power in e-commerce is only the initial, quick jab to an opponent’s face. Data-focused innovations in offline retail will be Amazon’s second, much heavier cross. Traditional retailers too focused on the jab aren’t seeing the cross coming. But we think canny retailers can fight back — and avoid getting KO’d. Here’s how.

The e-commerce jab starts with warehousing

Physical storage of goods has long been crucial to advances in commerce. Innovations here range from Henry Ford’s conveyor belt assembly line in 1910, to IBM’s universal product code (the “barcode”) in the early 1970s, to J.C. Penney’s implementation of the first warehouse management system in 1975. Intelligrated (Honeywell), Dematic (KION), Unitronics, Siemens and others further optimized and modernized the traditional warehouse. But then came Amazon.

After expanding from books to a multi-product offering, Amazon Prime launched in 2005. Then, the company’s operational focus turned to enabling scalable two-day shipping. With hundreds of millions of product SKUs, the challenge was how to get your pocket 3-layer suture pad (to cite a super-specific product Amazon now sells) from the back of the warehouse and into the shippers’ hands as quickly as possible.

Make no mistake: Amazon’s one-two retail punch will be formidable.

Amazon met this challenge at a time when automated warehouses still had massive physical footprints and capital-intensive costs. Amazon bought Kiva Systems in 2012, which ushered in the era of Autonomous Guided Vehicles (AGVs), or robots that quickly ferried products from the warehouse’s depths to static human packers.

Since the Kiva acquisition, retailers have scrambled to adopt technology to match Amazon’s warehouse efficiencies.  These technologies range from warehouse management software (made by LogFire, acquired by Oracle; other companies here include Fishbowl and Temando) to warehouse robotics (Locus Robotics, 6 River Systems, Magazino). Some of these companies’ technologies even incorporate wearables (e.g. ProGlove, GetVu) for warehouse workers. We’ve also seen more general-purpose projects in this area, such as Google Robotics. The main adopters of these new technologies are those companies that feel Amazon’s burn most harshly, namely operators of fulfillment centers serving e-commerce.

The schematic below gives a broad picture of their operations and a partial list of warehouse/inventory management technologies they can adopt:

It’s impossible to say what optimizations Amazon will bring to warehousing beyond these, but that may be less important to predict than retailers realize.

The cross: Modernizing the physical retail environment

Amazon has made several recent forays into offline shopping. These range from Amazon Books (physical book stores), Amazon Go (fast retail where consumers skip the cashier entirely) and Amazon 4-Star (stores featuring only products ranked four-stars or higher). Amazon Live is even bringing brick-and-mortar-style shopping streaming to your phone with a home-shopping concept à la QVC. Perhaps most prominently, Amazon’s 2017 purchase of Whole Foods gave the company an entrée into grocery shopping and a nationwide chain of physical stores.

Most retail-watchers have dismissed these projects as dabbling, or — in the case of Whole Foods — focused too narrowly on a particular vertical. But we think they’re missing Bezos’ longer-term strategic aim. Watch that cross: Amazon is mastering how physical retail works today, so it can do offline what it already does incredibly well online, which is harness data to help retailers sell much more intelligently. Amazon recognizes certain products lend themselves better to offline shopping — groceries and children’s clothing are just a few examples.

How can traditional retailers fight back? Get more proactive.

Those shopping experiences are unlikely to disappear. But traditional retailers (and Amazon offline) can understand much, much more about the data points between shopping and purchase. Which path did shoppers take through the store? Which products did they touch and which did they put into a cart? Which items did they try on, and which products did they abandon? Did they ask for different sizes? How does product location within the store influence consumers’ willingness to buy? What product correlations can inform timely marketing offers — for instance, if women often buy hats and sunglasses together in springtime, can a well-timed coupon prompt an additional purchase? Amazon already knows answers to most of these questions online. They want to bring that same intelligence to offline retail.

Obviously, customer privacy will be a crucial concern in this brave new future. But customers have come to expect online data-tracking and now often welcome the more informed recommendations and the convenience this data can bring. Why couldn’t a similar mindset-shift happen in offline retail?

How can retailers fight back?

Make no mistake: Amazon’s one-two retail punch will be formidable. But remember how important the element of surprise is. Too many venture capitalists underestimate physical retail’s importance and pooh-pooh startups focused on this sector. That’s extremely short-sighted.

Does the fact that Amazon is developing computer vision for Amazon Go mean that alternative self-checkout companies (e.g. Trigo, AiFi) are at a disadvantage? I’d argue that this validation is actually an accelerant as traditional retail struggles to keep up.

How can traditional retailers fight back? Get more proactive. Don’t wait for Amazon to show you what the next best-practice in retail should be. There’s plenty of exciting technology you can adopt today to beat Jeff Bezos to the punch. Take Relex, a Finnish startup using AI and machine learning to help brick-and-mortar and e-commerce companies make better forecasts of how products will sell. Or companies like Memomi or Mirow that are creating solutions for a more immersive and interactive offline shopping experience.

Amazon’s one-two punch strategy seems to be working. Traditional retailers are largely blinded by the behemoth’s warehousing innovations, just as they are about to be hit with an in-store innovation blow. New technologies are emerging to help traditional retail rally. The only question is whether they’ll implement the solutions fast enough to stay relevant.


Source: The Tech Crunch

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What would it mean to eradicate the mosquito?

Posted by on Apr 17, 2019 in Column, TC | 0 comments

From “blitzscaling” to “move fast and break things,” startups are focused on growth and speed – that’s change at scale. I see that focus in the startups in my accelerators and students in my classes at USC. But something related that we rarely talk seriously about is what happens when that growth, speed, and change affects other parts of an existing system. That’s deemed to be outside of our concern.

The business and social effects of change might be more commonly noticed, but today I want to talk about health effects, both positive and negative, that can come from a big and rapid change.

One of the preventable diseases that still kills a large number of people is malaria, spread by mosquitoes. Humans have dealt with this disease for centuries. Even in the US, malaria was only eradicated in 1951.

As high a toll as malaria takes, the number of annual deaths has decreased a lot. While in 2015 there were 212 million malaria cases and 429,000 deaths, just 20 years earlier the numbers were much higher, with estimates of 300 – 500 million cases with 3 million deaths.

The decrease in malaria deaths is multifactorial but mainly came from a few initiatives: the distribution of insecticide-treated bed nets, better medicines that can be taken temporarily, and the reduction of mosquito breeding sites like standing water.

While bed nets and medication have helped reduce human suffering and deaths due to malaria, it seems obvious to take the next step and try to eliminate malaria entirely. But since there is still no effective vaccine against the plasmodium parasite spread by mosquitoes plans for eliminating malaria often call for eradication of mosquitos, or specifically the Anopheles gambiae species that carry human malaria strains.

This approach — eradication of a targeted species that is the disease vector — is relatively uncommon. Some who question the approach warn against unintended consequences of such an effort. They are right to want to understand the larger effects, so the next questions are how do we make this decision? And are we cruel for not eradicating mosquitoes if we can? Would this decision be delayed if malaria were still a problem in the US? Do we even have the authority to attempt intentional species eradication? How do we even make these decisions?

The comparison that last question usually draws is that of smallpox eradication. When, in 1980, the disease was determined to be eliminated from human populations it was a triumph of decades of vaccinations and swift response to outbreaks.

SAO PAULO, BRAZIL – MARCH 04: Aedes aegypti mosquito, the species which transmits the dengue virus, chikungunya fever and zika is photographed on March 04, 2016 in Sao Paulo, Brazil. (Photo by William Volcov/Brazil Photo Press/LatinContent/Getty Images)c

There are several ways to attempt Anopheles gambiae eradication. Since mosquitoes have gained resistance to many classes of insecticides and the plasmodium parasites also have resistance to antimalarial drugs, other methods are used.

One way is the release of large numbers of sterilized males. This process was successfully applied to the screw-worm fly in the US in the 1950s. A similar approach could be taken with mosquitoes as well. It’s a temporary solution since even a small number of non-sterilized mosquitoes that manage to mate can rebuild a population. The Debug project has an ongoing trial of this technique with Aedes aegypti mosquitoes that carry Zika, yellow fever, and dengue fever.

There is also a program to use CRISPR gene editing to introduce genes for infertility into the mosquito population.

The approach taken with smallpox – too vaccinate the disease away – doesn’t work with malaria, at least not yet. Current versions of the vaccine require four separate inoculations spread over weeks. Even then the efficacy rate is around 39%. (And vaccines are a technique that would enable the mosquitoes to continue to bite humans, who are immune from malaria.) So that brings us back to the idea of eliminating mosquitoes.

A starting point to evaluate that decision is to take mosquitoes as part of a system that will change if they are eliminated. Taking a whole systems approach isn’t so much delaying a solution as it is trying not to create a new problem by the quick actions mentioned above.

The other side of the equation is that malaria-carrying mosquito species are not large sources of food for other animals. The non-biting males are among the many insects that pollinate different types of plants, but are only major pollinators of one type of orchid. Note also that biologist E. O. Wilson is in favor of mosquito eradication.

But if malaria-carrying mosquito eradication happens, there are other potential negative outcomes. At least one of them could affect more than the current number of people dying from malaria today.

People change their habits. Without mosquitoes keeping the human population away from prime mosquito habitats like swamps and rain forests, more people may move to these areas. People may then push out other animals and prepare unoccupied lands for logging and farming. Also, people may hunt and eat more “bush meat,” a source of other cross-species diseases, including Ebola and AIDS.

Stating the potential negatives of eliminating malaria is easy outside of a malaria infected area. Could we make an attempt at estimating potential deaths from both options?


Source: The Tech Crunch

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Get ready for a new era of personalized entertainment

Posted by on Apr 13, 2019 in Amazon, Artificial Intelligence, Column, computing, Content, Facebook, machine learning, Marketing, Multimedia, personalization, smart devices, Spotify, Streaming Media, streaming services, Twitter, virtual reality, world wide web | 0 comments

New machine learning technologies, user interfaces and automated content creation techniques are going to expand the personalization of storytelling beyond algorithmically generated news feeds and content recommendation.

The next wave will be software-generated narratives that are tailored to the tastes and sentiments of a consumer.

Concretely, it means that your digital footprint, personal preferences and context unlock alternative features in the content itself, be it a news article, live video or a hit series on your streaming service.

The title contains different experiences for different people.

From smart recommendations to smarter content

When you use Youtube, Facebook, Google, Amazon, Twitter, Netflix or Spotify, algorithms select what gets recommended to you. The current mainstream services and their user interfaces and recommendation engines have been optimized to serve you content you might be interested in.

Your data, other people’s data, content-related data and machine learning methods are used to match people and content, thus improving the relevance of content recommendations and efficiency of content distribution.

However, so far the content experience itself has mostly been similar to everyone. If the same news article, live video or TV series episode gets recommended to you and me, we both read and watch the same thing, experiencing the same content.

That’s about to change. Soon we’ll be seeing new forms of smart content, in which user interface, machine learning technologies and content itself are combined in a seamless manner to create a personalized content experience.

What is smart content?

Smart content means that content experience itself is affected by who is seeing, watching, reading or listening to content. The content itself changes based on who you are.

We are already seeing the first forerunners in this space. TikTok’s whole content experience is driven by very short videos, audiovisual content sequences if you will, ordered and woven together by algorithms. Every user sees a different, personalized, “whole” based on her viewing history and user profile.

At the same time, Netflix has recently started testing new forms of interactive content (TV series episodes, e.g. Black Mirror: Bandersnatch) in which user’s own choices affect directly the content experience, including dialogue and storyline. And more is on its way. With Love, Death & Robots series, Netflix is experimenting with episode order within a series, serving the episodes in different order for different users.

Some earlier predecessors of interactive audio-visual content include sports event streaming, in which the user can decide which particular stream she follows and how she interacts with the live content, for example rewinding the stream and spotting the key moments based on her own interest.

Simultaneously, we’re seeing how machine learning technologies can be used to create photo-like images of imaginary people, creatures and places. Current systems can recreate and alter entire videos, for example by changing the style, scenery, lighting, environment or central character’s face. Additionally, AI solutions are able to generate music in different genres.

Now, imagine, that TikTok’s individual short videos would be automatically personalized by the effects chosen by an AI system, and thus the whole video would be customized for you. Or that the choices in the Netflix’s interactive content affecting the plot twists, dialogue and even soundtrack, were made automatically by algorithms based on your profile.

Personalized smart content is coming to news as well. Automated systems, using today’s state-of-the-art NLP technologies, can generate long pieces of concise, comprehensible and even inventive textual content at scale. At present, media houses use automated content creation systems, or “robot journalists”, to create news material varying from complete articles to audio-visual clips and visualizations. Through content atomization (breaking content into small modular chunks of information) and machine learning, content production can be increased massively to support smart content creation.

Say that a news article you read or listen to is about a specific political topic that is unfamiliar to you. When comparing the same article with your friend, your version of the story might use different concepts and offer a different angle than your friend’s who’s really deep into politics. A beginner’s smart content news experience would differ from the experience of a topic enthusiast.

Content itself will become a software-like fluid and personalized experience, where your digital footprint and preferences affect not just how the content is recommended and served to you, but what the content actually contains.

Automated storytelling?

How is it possible to create smart content that contains different experiences for different people?

Content needs to be thought and treated as an iterative and configurable process rather than a ready-made static whole that is finished when it has been published in the distribution pipeline.

Importantly, the core building blocks of the content experience change: smart content consists of atomized modular elements that can be modified, updated, remixed, replaced, omitted and activated based on varying rules. In addition, content modules that have been made in the past, can be reused if applicable. Content is designed and developed more like a software.

Currently a significant amount of human effort and computing resources are used to prepare content for machine-powered content distribution and recommendation systems, varying from smart news apps to on-demand streaming services. With smart content, the content creation and its preparation for publication and distribution channels wouldn’t be separate processes. Instead, metadata and other invisible features that describe and define the content are an integral part of the content creation process from the very beginning.

Turning Donald Glover into Jay Gatsby

With smart content, the narrative or image itself becomes an integral part of an iterative feedback loop, in which the user’s actions, emotions and other signals as well as the visible and invisible features of the content itself affect the whole content consumption cycle from the content creation and recommendation to the content experience. With smart content features, a news article or a movie activates different elements of the content for different people.

It’s very likely that smart content for entertainment purposes will have different features and functions than news media content. Moreover, people expect frictionless and effortless content experience and thus smart content experience differs from games. Smart content doesn’t necessarily require direct actions from the user. If the person wants, the content personalization happens proactively and automatically, without explicit user interaction.

Creating smart content requires both human curation and machine intelligence. Humans focus on things that require creativity and deep analysis while AI systems generate, assemble and iterate the content that becomes dynamic and adaptive just like software.

Sustainable smart content

Smart content has different configurations and representations for different users, user interfaces, devices, languages and environments. The same piece of content contains elements that can be accessed through voice user interface or presented in augmented reality applications. Or the whole content expands into a fully immersive virtual reality experience.

In the same way as with the personalized user interfaces and smart devices, smart content can be used for good and bad. It can be used to enlighten and empower, as well as to trick and mislead. Thus it’s critical, that human-centered approach and sustainable values are built in the very core of smart content creation. Personalization needs to be transparent and the user needs to be able to choose if she wants the content to be personalized or not. And of course, not all content will be smart in the same way, if at all.

If used in a sustainable manner, smart content can break filter bubbles and echo chambers as it can be used to make a wide variety of information more accessible for diverse audiences. Through personalization, challenging topics can be presented to people according to their abilities and preferences, regardless of their background or level of education. For example a beginner’s version of vaccination content or digital media literacy article uses gamification elements, and the more experienced user gets directly a thorough fact-packed account of the recent developments and research results.

Smart content is also aligned with the efforts against today’s information operations such as fake news and its different forms such as “deep fakes” (http://www.niemanlab.org/2018/11/how-the-wall-street-journal-is-preparing-its-journalists-to-detect-deepfakes). If the content is like software, a legit software runs on your devices and interfaces without a problem. On the other hand, even the machine-generated realistic-looking but suspicious content, like deep fake, can be detected and filtered out based on its signature and other machine readable qualities.


Smart content is the ultimate combination of user experience design, AI technologies and storytelling.

News media should be among the first to start experimenting with smart content. When the intelligent content starts eating the world, one should be creating ones own intelligent content.

The first players that master the smart content, will be among tomorrow’s reigning digital giants. And that’s one of the main reasons why today’s tech titans are going seriously into the content game. Smart content is coming.


Source: The Tech Crunch

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The two forces reshaping the landscape of shipping and logistics

Posted by on Mar 28, 2019 in Column, Convoy, keeptruckin, Logistics, Samsara, Shipping, TC, Transfix, trucking, uber freight | 0 comments

The shipping and logistics space is being rapidly transformed by technology. Innovations in this space span the way buyers and sellers transact (digital freight brokerages), the way goods are monitored during shipment (sensor-enabled real-time monitoring) and the manner in which risk is managed (novel approaches to pricing insurance). With diverse opportunities like these, it is no surprise that this is a space ripe for significant disruption.

And yet technology is not the only force driving change. Regulators are taking a fresh look at the lives of workers in the gig economy, often concluding that many folks classified as independent contractors ought to be treated as employees. As we will see, this is causing a sharp uptick in the creation of small-motor carriers. At the same time, oddly enough, driver scarcity is forcing innovators in the shipping and logistics space to think very hard about how to entice new drivers into the market.

Two forces — driver scarcity and regulation — are working in unison to forge the shipping and logistics space of tomorrow. Before we dive into precisely how this is happening, let me introduce the dramatis personnae in this ecosystem:

  • Shippers — These are the folks who have goods that need to be moved from point A to point B.
  • Carriers — These are the folks who shippers hire to load goods on a truck and move them from point A to point B. I will use carriers and small-motor carriers as interchangeable terms.
  • Brokers — These are the people who connect shippers with carriers, often doing the hard work of making sure that carriers are properly licensed and have the appropriate levels of insurance.
  • FMCSA — Federal Motor Carrier Safety Administration, the body responsible for facilitating safety programs, licensing motor carriers and ensuring compliance with a wide range of shipping and transportation rules and regulations.  

A tale of software and shipping

Today, shipping runs on a backbone of telephone calls, manual logging and delayed payment. Yet the shipping ecosystem of the future will have an entirely different nervous system. Before we examine how driver scarcity and regulation will shape this future system, let’s consider where we are today.

Historically, the shipping industry functions on the basis of trust and deep-rooted professional relationships. The largest shippers have relied for a very long time on an entrenched broker network that connects them with carriers capable of moving cargo reliably at scale. Brokers are paid for reducing risk for the shippers by properly vetting the carriers. These relationships form the nervous system of the traditional trucking industry.

This traditional approach to shipping is being disrupted by a number of well-well-funded, ambitious startups. Companies like Samsara, Convoy, and Freight Rover are introducing next-generation hardware, software tools and other solutions to optimize shipping at scale. These companies have different theses about how to properly optimize shipping tasks, but the common thread is that they all appreciate the need to leverage new technology to remove unnecessary friction between ecosystem actors.

The wake of disruption is going to benefit everyone in the shipping and logistics space.

Carriers will get two important benefits: (1) instant access to shipping jobs and (2) a data platform for managing and understanding their businesses. Shippers will also receive two things essential to optimizing their revenue — (i) a constant supply of reliable carriers and (ii) a wealth of real-time data about live and legacy shipments.

The role of regulation

Against the background of the disruption described above, there has been a lot of regulatory activity affecting the shipping and logistics space. In general, the government is becoming more active in regulating the way in which the shipping industry runs, especially when it comes to the treatment of drivers and the unreasonable demands often imposed on them by aggressive shipping schedules.

The first change came from Congress at the end of 2017 in what is known as the Electronic Logging Device (or ELD) mandate. In a nutshell, the ELD mandate requires carriers to have an approved logging device in their trucks to ensure that their hours of service are properly logged and available for regulator review.

This is surely just the beginning of regulatory activity. Not only has Congress expressed interest in closely monitoring Hours of Service — the amount of consecutive hours a truck driver may lawfully drive — the ELD mandate is widely viewed as a way to better enforce those rules.

Thus, at the federal level, you have a regulator who wants to keep granular tabs on what truck drivers are doing. What about at the state level, what’s going on there?

At the state level, many states are adopting laws that require an employer (including shippers and carriers) to classify someone as an employee if he or she provides services for the employer’s core business. In short, if the employer’s core business is X and a person is hired to do X, then that person is an employee.

In California, for example, this is known as the ABC Test from the Dynamex decision handed down by the California Supreme Court. In that case, Dynamex believed they could lawfully classify their delivery drivers as independent contractors. The benefit of doing so is that independent contractors are not entitled to key employee benefits, including healthcare and expense reimbursements. The California Supreme Court decided that Dynamex made a mistake in not classifying these drivers as employees.

Developments like the ABC Test are already transforming the shipping world. Under this test, a driver is almost always going to be legally entitled to the status of “employee” because a driver in the shipping world is by definition being hired to fulfill the core business activities of the shipper.

So, let’s combine the regulatory developments happening at the state and federal level. At the federal level, Congress is encouraging the rapid adoption of monitoring technologies like ELDs. At the state level, employers are facing pressure to classify drivers as employees. Increased tech-based monitoring is thus occurring at the same time that drivers are getting increased rights to employee benefits at the state level.

This is a big deal. Drivers are getting increased leverage vis-à-vis their employers, while the employers (i.e. shipping companies and carrier owners) are being required to use safety-enhancing monitoring technologies. Regulation is moving in one direction — toward providing a greater degree of protection for truckers.


Source: The Tech Crunch

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Autonomous vehicle IP protection — when HAL is driving

Posted by on Mar 28, 2019 in Automotive, Column, intellectual property, TC, Transportation | 0 comments

Each day, a fleet of lidar-guided, all-electric Chevy Bolts exits a downtown garage to roam San Francisco, attempting to blend in with people-guided vehicles and other AVs. The autonomous vehicles are actually only “semi-autonomous” — each has a human crew whose mission is to correct the car’s erroneous driving decisions on the fly, until sufficient data can at least approximate the reflexive intuition of an experienced driver.

Like a child who develops a sense for right and wrong through praise and scolding, present-day machine learning requires similar binary experiential training. The collected learning then becomes a valuable basis for guidance systems that will render vehicles truly autonomous.

But how can that very valuable intellectual property be protected? Historically, startups could obtain venture capital by trotting out a portfolio of issued patents. With the 2014 Alice decision on subject matter patentability by the U.S. Supreme Court, however, it has been problematic, to say the least, to obtain patents that are essentially based on algorithms.

The two-step “Alice” test requires examination of 1) whether the claims are directed to a patent-eligible concept or a patent-ineligible abstract idea; and 2) if directed to an abstract idea, whether the claims contain an “inventive concept” sufficient to transform the abstract idea into a patent-eligible application. Under the latter, “well-understood, routine, and conventional” activities or claim elements cannot form an inventive concept. Even if subject matter barriers can be overcome, the evolved AI may no longer bear semblance to the original expression of code, such as to raise inventorship issues. If a macaque monkey cannot hold a copyright, can a machine hold a patent?   

As a result, most companies presently guard their machine learning data as trade secrets. But trade secret protection has its drawbacks, one of which is to society at large. Unlike technology taught in patented disclosures, which could allow a new entrant to catch up (provided it licenses or designs around the patent), an AV data set of an unwilling licensor is not obtainable absent a trade secret violation or duplicating the considerable miles driven. 

Keeping AV data secret also creates a “black box” where consumers and authorities are unable to fairly and completely evaluate the proficiency/safety of the AI systems guiding the vehicles. At most, consumers will likely have to rely on publicly compiled data regarding car crashes and other reported incidents, which fail to adequately assess the underlying AI or even isolate AI as the cause (as opposed to other factors). As it is, AV developers’ “disengagement reports” — those tallying incidents where the human attendant must take over for the AI — vary widely, depending on how the developer chooses to interpret the reporting requirement.  Without comparable data, consumers are often left with nothing more than anecdotal evidence as to which AV system is the safest or most advanced.

Trade secret protection has its drawbacks, one of which is to society at large.

Relying on trade secret protection is also problematic for the owner of the data, largely because of the requirement that to be protectable, the trade secrets must be kept confidential. This can lead to a “need-to-know” access environment, hampering development and breeding paranoia. Physical security could mean preventing employees from carrying data on portable devices or working from home, instead requiring work and storage on servers isolated from external connectivity. It also could mean needing metal detectors and security screening devices and procedures to, quite literally, keep data from walking out the door. Encryption also could be used, introducing yet another layer of protection, but possibly with a productivity trade-off. And none of this is a complete guard against a mal-intended employee who abuses their access privileges.  

And what of that disgruntled employee who, instead of taking an unauthorized copy to another employer, virally transmits it over social media? Once out in public, the secrets lose their value, as present law generally does not permit actions against a company that comes across trade secrets through no fault of their own. Imagine losing your company’s valuation because your once-proprietary AV data set is now essentially public domain.

On the other hand, one might question whether the “best” AI should be kept from the public. A promise of AVs is that AI guidance and inter-vehicle communications can enhance traffic safety and optimize traffic flow.  Confining the safest, highest functioning AI to select manufacturers would mean less-than-optimal overall safety or efficiency, as “smarter” cars would need to deal with “less smart” vehicles (and human-driven ones!). At the very least, without any technical standards regulating the interaction between various AVs, each unique system will need to communicate with, and predict the behaviors of, potentially hundreds of different AIs.

All of this is to suggest that, as present-day human-driven vehicles evolve into the Nikola 9000, our IP laws and protections must likewise evolve. Just as hybrid vehicles were an early solution to “range anxiety,” perhaps some hybrid IP concept could be developed to satisfy the needs for autonomous vehicle IP protection while continuing to “promote the progress of science and useful arts” under the Constitution.


Source: The Tech Crunch

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Demanding privacy, and establishing trust, in digital health

Posted by on Mar 26, 2019 in Column, digital health, Health, Privacy | 0 comments

February’s Wall Street Journal report pulled back the curtain on just how much is at stake when individuals share their personal health information with health and fitness applications. Several of these apps were (perhaps unwittingly) sharing users’ personal health information via a Facebook SDK that was automatically feeding that data to the platform. In one fell swoop, multiple companies damaged trust with their users — perhaps irrevocably.

But the dangers in digital health aren’t limited to rogue SDKs; three days after the Facebook news broke, yet another large health system announced the personal information of more than 325,00 patients had been exposed. All this comes as big tech companies like Apple, IBM and Amazon begin to enter the same space, with plans for huge impact. But even these well-established names enter healthcare with a trust deficit; Rock Health’s 2018 National Consumer Health Survey found that just 11 percent of respondents said they’d be willing to share health data with tech companies.

As we move toward an increasingly digitized world of healthcare — and as early-stage companies and tech behemoths operate alongside one another in the space — how can all involved uphold their responsibilities, follow relevant laws and regulations and maintain the trust of patients and users when it comes to privacy? Companies operating under the highest standards in healthcare are expressly prohibited from monetizing users’ data; how will large tech brand names adapt their business models to act properly?

In order for the promise of digital health to be realized, companies will need to ensure their patients’ data is safe, secure and error-free. Beyond security, healthcare companies operating as providers must also maintain the confidentiality and privacy of that data. Doing so isn’t simply good practice; it’s an existential requirement for companies operating in this space. There is a baseline expectation — from users, and from employers and health plans working with digital health companies — of privacy being maintained.

The success of digital health companies will hinge on whether patients feel comfortable sharing the most intimate data they possess — their personal health information (PHI) — especially when they worry that data could impact their employment. Below are three things digital health companies would do well to keep in mind as they operate in the space.

Comply with — and inform — regulations

In 2018 alone, more than 6.1 million individuals were impacted by healthcare data breaches. Many have started to warn of the “data breach tsunami.” Complacency is no longer viable. The increasing frequency of data breaches should become a rallying cry. When it comes to PHI, protecting the privacy and security of patients and users must be a business imperative.

Patients want to focus on getting better, not having to constantly check their privacy settings.

Complying with regulations and requirements for protecting PHI requires a combination of robust privacy and security strategies. The Health Insurance Portability and Accountability Act (HIPAA) sets the baseline for patient data protection. For companies operating under HIPAA, responsibilities, obligations and opportunities become crystal clear. Federal laws and regulations prescribe privacy and security minimums, as well as the exact rules governing collection, storage and transfer of participant data. For health innovators, strong privacy practices and security controls are key to customer trust and to growth.

This also means that digital health companies must be active participants in shaping the regulations that govern their operations. This isn’t a call to hire as many lobbyists as possible to water down your responsibilities; it’s a demand to educate the state and federal policymakers who will be writing the rules of the road that govern your work for the next phase of healthcare. Informed policy that enables creative iteration while putting the needs of the patient at its center is imperative for the continued success of the entire industry. This is a space where regulations can be helpful in clearly identifying what not to do to be taken seriously — and operate properly — as a digital health company.

HIPAA or not: know your role

HIPAA applies to digital health companies — whether they contract as a vendor (a “business associate”) or a healthcare provider (a “covered entity”). Third-parties, especially those that handle PHI, have the potential of exposing health companies to data breaches and non-compliance. Any data breach suffered by a healthcare company will have serious consequences, including reputational damage, government investigations and monetary damages.

Once credibility has been tarnished, it takes significant time to rebuild trust among consumers. Fundamental to this is understanding the difference between operating in technology broadly versus in digital health, and ensuring that your organization is equipped with a deep understanding of all the ins-and-outs of HIPAA and health care data; patients want to focus on getting better, not having to constantly check their privacy settings.

Keep compliance at your core

The healthcare industry is already fraught with risk. New laws and market forces only add to the complexities. In order to reach full maturity, digital health companies need to invest, early, in information security experts who understand the intersection of medical devices, software and regulations. Senior leadership teams must empower these experts while staying engaged on best practices and the latest threats. This goes against the rapid growth mindset of venture-backed companies in other industries, but is critical when it comes to healthcare.

If you are handling patient data, hiring a legal and compliance team is a top priority. By implementing a privacy and compliance program, you’ll be better equipped to find and correct potential vulnerabilities, while reducing the chance of fraud, and promoting safe and quality care.

The responsibility to establish trust in digital health is on the most prominent actors in a rapidly growing space. Data and its proper application hold the keys to the evolution of healthcare. But we must never forget that patients and users are opting to share the most intimate data they have. We must meet that responsibility with the systems, personnel and maturity it deserves.


Source: The Tech Crunch

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