• Thinking of Self-Studying Machine Learning? Remind yourself of these 6 things

    I’m a self-taught¹ Machine Learning Engineer, here’s what I’d tell myself if I started againWhere most of my self-study takes place. Photo from: Daniel Bourke on YouTube.We were hosting a Meetup on robotics in Australia and it was question time.Someone asked a question.“How do I get into artificial intelligence and machine learning from a different background?”Nick turned and called my name.“Where’s Dan Bourke?”I was backstage and talking to Alex. I walked over.“Here he is,” Nick continued, “Dan comes from a health science background, he studied nutrition, then drove Uber, learned machine learning online and has now been with Max Kelsen as a machine learning engineer for going on a year.”Nick is the CEO and Co-founder of Max Kelsen, a technology company in Brisbane.I stood and kept listening.“He has (...)

    #data-science #machine-learning #online-learning #machine-learning-course #study-machine-learning

  • #startup Aggregation Opportunities: Order Ahead & Contact Info / Social Graph Hub

    Just four months after my experiment of deleting every app from my phone for 30 days, I’m disappointed to admit that I’m back up to 70 apps. Although this is still 66 fewer than when I originally deleted everything, it’s still too many. Frankly, I’m a bit envious of the Chinese “Super-Apps” like WeChat, which aggregate messaging, ride-sharing, e-commerce, gaming, and more functions in one unified app. I don’t expect a U.S. version of the “super-app” to emerge anytime soon, as each of these functions serve as the focus of the most valuable U.S. #tech companies (Facebook / Apple, Uber / Lyft, Amazon, etc.). But as Jim Barksdale, the former CEO of Netscape famously stated, “there are only two ways to make money in business: One is to bundle; the other is unbundle.”In the mobile-app world, I think (...)

    #startup-aggregation #venture-capital #startup-opportunities

  • The Live Stream Hack with Peter Yang formerly of Twitch

    Episode 23 of the Hacker Noon #podcast: An interview with Peter Yang, former Product Manager at Twitch.Today’s show would not be possible without Digital Ocean.Listen to the interview on iTunes, or Google Podcast, or watch on YouTube.In this episode Trent Lapinski and Peter Yang discuss the live streaming market including the differences between the US and Chinese markets, video game streaming, and product management.“Live streaming is about long form content, interactive content, content you can talk to your viewers about or talk to other streamers about.”“It is about creating these jobs for people who might not enjoy a white collar job, or driving Uber or something, who just really enjoy playing videos.”“Why not make a career out of playing video games? Being able to connect with other people (...)

    #videogames #product-management #hackernoon-podcast #live-streaming

  • The Cult Of Personality And How You Are Harmed

    Musk On The Cover Of Ashlee Vance’s BiographyThe cult of personality is waging a war in your mind but you many not even be aware of its existence.The cult of personality is designed to stunt your growth and I’m about to show you how. The cult of personality is best personified by none other than Elon Musk. I never thought I’d be #writing this kind of article because I may be one of the biggest fans of Elon Musk. In fact, three years ago, when I came across one of his videos by accident, it was much like being struck by lightning. My mind went on fire. Last year, I even sent Musk a custom-designed portfolio that contained a proposal for Uber drivers to be paired with Teslas.I have a long tradition of sending things to people I greatly admire and respect. I’ve been doing this since I was a (...)

    #media #personal-development #elon-musk #self-improvement

  • The world’s 310 unicorns are valued at over $1,000 billion

    According to CB Insights’ unicorn tracker, unicorns have raised a combined total of nearly $257 billion.Data by #startup and venture capital intelligence firm CB Insights show a total of 310 private companies around the world valued at more than $1 billion as of January 2019. Last year, 112 new companies joined the global unicorn club, a 58% increase from the 71 new unicorns in 2017.The collective worth of all unicorns currently identified by CB Insights — and published in a new infographic under 13 categories — is $1,052 billion. They have raised a combined total of nearly $257 billion.Credits: CB InsightsThe top 10 unicorns by market value are:Bytedance (valued at $75 billion)Uber ($72 billion)Didi Chuxing ($56 billion)WeWork ($47 billion)Airbnb ($29.3 billion)SpaceX ($21.5 billion)Palantir and (...)

    #tech-unicorns #all-tech-unicorns #all-unicorn-companie #how-many-tech-unicorn

  • La justice cuisine Uber

    Le combat entamé par des autoentrepreneurs pour faire reconnaître leur plateforme de transport ou de livraison comme des employeurs commence à porter ses fruits devant les tribunaux. L’étau se resserre autour des plateformes. Jeudi, un arrêt de la cour d’appel de Paris a reconnu le lien de subordination entre un chauffeur VTC et la société Uber, estimant que ce qui les unissait était bien un « contrat de travail ». Une décision de justice historique pour les travailleurs « ubérisés », qui considèrent (...)

    #Deliveroo #Foodora #Uber #travail #législation #procès #travailleurs #surveillance (...)


  • A Progressive Web App in Vue #tutorial , Part 1 — The Vue App

    The BasicsBuild a Progressive Web App In #vuejs, from Zero to Hero!The concept of Progressive Web Apps (PWAs) is a framework agnostic approach which seeks to combine discoverability and accessibility of a website with the functionality of a native app.Since couple of years I see an increasing interest technologies which bridge the gap between web- and native-apps.In 2018 PWAs have made a great step towards mainstream adoption. By now, plenty of companies like Pinterest, Uber, Twitter, Trivago, The Washington Post, Starbucks, have already created PWAs to run parallel to their native apps.The reason is obvious, plenty of these companies report very promising numbers, mostly as astonishing as the 97 percent of increase in conversions Trivago has seen.Why should we start developing PWAs now?In (...)

    #web-development #pwa #javascript

  • #rabbitmq, #amqp, #mqtt & Rest of the world

    Hey folks, welcome back. Hope you all are doing well. Then why wasting time ! Lets move to the tutorial.Today I am going to write on Message Queue. Very simple nah ? Huh lets dive.These days we are developing smart applications to make lives easier. There are lots of tech giants with lots of tech engineers fighting to solve problems. There are Google, Facebook, Pathao, Uber, Grab, AirBnB and so on….A common task we developers do is send notifications or requests to process tasks between applications. One of the solution to do it could be using Message Queue.RabbitMQ : RabbitMQ is a message queueing hybrid broker. Hybrid is that sense it has support for different protocols like AMQP, MQTT, WebSocket etc.AMQP ( Advanced Message Queueing Protocol ) : is an open standard application layer (...)

    #software-engineering #message-queue

  • Taxi 2.0: The Bumpy Road to the Future of Cabs - Motherboard

    After a typical honeymoon period of unquestioning and often oblivious tech culture praise, Uber and its taxi app brethren are getting some real, overdue scrutiny. Thank cabbies in part, for highlighting the fact that much of Uber’s business model success has to do with bypassing basic taxi regulations, safety checks, and continuous commercial insurance coverage, in a monoplistic bid for all sides of the taxi market. Protests and lawsuits and injunctions now follow close behind these companies into nearly every new city they zoom into, with the requisite lawyers and lobbyists in the backseat.

    At the same time, anyone who’s experienced a city knows that licensed taxi companies are due for an upgrade, and maybe some of these apps’ success has to do with the old industry’s disinterest in adaptation. Shutting out the Uber model—and its rather edgier “rideshare” kin, like Lyft and SideCar and UberX—from the ride-for-hire ecosystem is as poor an answer as allowing it to persist without the institution of new checks and rules.

    In the short documentary “Taxi 2.0,” filmmaker Max Maddox attacks the issue from street-level in San Francisco by talking to taxi and Uber and Lyft drivers and the people that use each. No one comes away looking great. Everyone’s trying to figure out what it all means. (Where, exactly, is the sharing in this sharing economy? And how are these taxis called “rideshares” when there’s no real ride-sharing going on?) Apart from concerns about unfair competition, says Maddox, “taxi proponents say these rideshares are unsafe for the public. In the midst of this drama, drivers on both sides of the playing field struggle just to put bread on the table.”

    Here we see the specter not only of a new labor war in the taxi industry, between established hacks and amateur upstarts armed with GPS maps, but a of a stratified ride-for-hire future, in which taxis are left carrying the unconnected lower classes, while Uber and the like carry the relative big money. Technology has a way of dividing us like that.

    I usually feel half-guilty when I get in a TNC, but the cab system is far from perfect at the same time.

    Maddox, a broadcasting student at San Francisco State University whose interest was piqued after seeing “so many mustached cars drive by,” came away from the months-long project with mixed feelings about the future of cabs.

    “After interviewing all these guys, I’m still on the fence about transportation network companies, or rideshares, whatever you want to call them,” Maddox says. “I usually feel half-guilty when I get in a TNC, but the cab system is far from perfect at the same time. I can’t endorse one platform over the other. I just hope something changes so they can coexist.”

    ’Taxi 2.0’ Credits: Producer: Max Maddox; Editor: Jarod Taber; Photographer: Asger Ladefoged; Writer: Ben Mitchell; Sound: Gabe Romero Associate Producer: Jason Garcia

    #Taxi #Uber #USA #San_Francisco

  • Apache #spark — Tips and Tricks for better #performance

    Apache Spark — Tips and Tricks for better performanceApache Spark is quickly gaining steam both in the headlines and real-world adoption. Top use cases are Streaming Data, Machine Learning, Interactive Analysis and more. Many known companies uses it like Uber, Pinterest and more. So after working with Spark for more then 3 years in production, I’m happy to share my tips and tricks for better performance.Lets start :)1 - Avoid using Custom UDFs:UDF (user defined function) :Column-based functions that extend the vocabulary of Spark SQL’s DSL.Why we should avoid them?From the Spark Apache docs:“Use the higher-level standard Column-based functions withDataset operators whenever possible before reverting tousing your own custom UDF functions since UDFs are ablackbox for Spark and so it does not even (...)

    #tuning #apache-spark #big-data

  • Uberland : l’avenir du travail à l’heure des algorithmes |

    Dans Uberland : comment les algorithmes réécrivent les règles du travail (2018, Presse universitaire de Californie, non traduit), la chercheuse Alex Rosenblat (@mawnikr) a synthétisé quatre années de recherche ethnographique avec les conducteurs d’Uber. Un livre où transparaît une vision dystopique du travail où des millions de conducteurs sont gérés par un système technique qui combine à la fois l’autoritarisme du management scientifique à la Frederick Taylor et le leadership cynique d’un Michael Scott (le personnage incarné par Steve Carell dans la série The Office), rapporte Intelligencer.

    (...) Le mot entrepreneur cache de plus en plus souvent un travailleur sans salaire minimum, sans avantages sociaux ni protection. L’absence de hiérarchie signifie que les indépendants sont soumis aux caprices de système de notation anonymes. Dans l’économie du partage, personne n’est licencié, les conducteurs sont « désactivés », sans que ce processus ne soit ni juste ni transparent. Les interactions humaines authentiques que vantaient les plateformes ont surtout créé de la paupérisation. L’évolution de l’économie du partage, comme de l’industrie de la techno, a commencé par un rêve utopique et s’achève dans un cauchemar dystopique. Les entreprises qui annonçaient vouloir changer le monde, comme Airbnb et Uber, ont visiblement été construites sur des idéaux qui ont atteint leur date d’expiration, conclut Mike Bulajewski. Si l’ubérisation n’est peut-être pas encore tout à fait morte, la lutte contre ses effets, elle, ne cesse de s’organiser.

    #futur_du_travail #économie #algorithme #économie_du_partage

  • We’ve Been Trapped in ‘Uberland’

    In her new book, Alex Rosenblat talked with drivers in 25 cities to trace the story of how ride-hailing redefined the nature of work. In 2009, Uber was born out of a simple idea : Tap a button, get a ride. As it grew popular, the platform, and the ride-hailing model it helped pioneer, seemed like it would go beyond just meeting a transportation need : It seemed to have the potential to solve problems of transit access and cater to people whom cab drivers may have discriminated against in (...)

    #Uber #travail

  • 5 Questions to Ask While Building Your Marketplace Platform

    Building a marketplace setup is a tough nut to crack — and this is no breaking news.Although the model works extremely well at scale — for example, eBay, Airbnb, and Uber, among others — but getting to scale is another challenge altogether.It’s not something that’s achieved overnight, or without thorough planning. For instance, it took Wattpad, a community of writers and readers, around three years to get 300,000 uploads. Then, it took them only three more years to reach the 10 million mark. Similarly, the crowdfunding platform, Indiegogo, was founded in 2007, but it took them four years for their first big break.However, building an online marketplace does seem like a lucrative business option. Even more so, when you realize that global #marketplaces are set to own around 40% of the online retail (...)

    #ecommerce-marketplace #ecommerce #startup #online-marketplace

  • NYC passes minimum pay wage for Uber and Lyft drivers

    12.04.18 - New York City’s Taxi and Limousine Commission voted today to establish a minimum wage for drivers working for companies like Uber, Lyft, Juno and Via. The city is the first in the US to set a minimum pay rate for app-based drivers. Going forward, the minimum pay will be set at $17.22 per hour after expenses, bringing it in line with the city’s $15 per hour minimum wage for typical employees, which will take effect at the end of the year. The additional $2.22 takes into account contract drivers’ payroll taxes and paid time off.

    “Today we brought desperately needed relief to 80,000 working families. All workers deserve the protection of a fair, livable wage and we are proud to be setting the new bar for contractor workers’ rights in America,” Jim Conigliaro, Jr., founder of the Independent Drivers Guild, said in a statement. “We are thankful to the Mayor, Commissioner Joshi and the Taxi and Limousine Commission, City Council Member Brad Lander and all of the city officials who listened to and stood up for drivers.”

    Earlier this year, the Taxi and Limousine Commission released the results of a study it requested, which recommended the new pay floor. And in August, NYC Mayor Bill de Blasio signed a bill requiring the commission to set a base pay rate. The Independent Drivers Guild, which has been working towards a minimum pay rate for some time, estimates that contract drivers in the city are currently earning just $11.90 per hour after expenses.

    Across the US, there’s been increased scrutiny on what companies like Uber and Lyft are actually paying their workers. In May, San Francisco subpoenaed the two companies for their pay records, and both companies have faced lawsuits over driver wages. Last year, NYC began requiring all ride-hailing services to offer an in-app tipping option.

    The rules passed today aren’t sitting well with the companies affected by them, however. Lyft told Engadget that it’s concerned that calculating pay per ride rather than per week will incentivize short rides over long rides. Further, Lyft says the new out of town rates — which require companies to pay drivers more when they take passengers outside of the city and return without a passenger — will be hard to implement before the new regulations take effect in 30 days.

    “Lyft believes all drivers should earn a livable wage and we are committed to helping drivers reach their goals,” the company told Engadget. “Unfortunately, the TLC’s proposed pay rules will undermine competition by allowing certain companies to pay drivers lower wages, and disincentive drivers from giving rides to and from areas outside Manhattan. These rules would be a step backward for New Yorkers, and we urge the TLC to reconsider them.”

    Uber released a statement as well ahead of today’s vote. The company’s director of public affairs, Jason Post, said:

    “Uber supports efforts to ensure that full-time drivers in NYC - whether driving with taxi, limo or Uber - are able to make a living wage, without harming outer borough riders who have been ignored by yellow taxi and underserved by mass transit.

    The TLC’s implementation of the City Council’s legislation to increase driver earnings will lead to higher than necessary fare increases for riders while missing an opportunity to immediately reduce congestion in Manhattan’s central business district.

    The TLC’s rules does not take into account incentives or bonuses forcing companies to raise rates even higher. Companies use incentives and bonuses as part of driver earnings to ensure reliability citywide by providing a monetary incentive to drivers to complete trips in areas that need them the most (such as outside of Manhattan).

    In addition, the rules miss an opportunity to immediately deal with congestion in Manhattan’s central business district. A recent TLC study authored by economists James Parrott and Michael Reich describes a formula that would financially punish companies who have low utilization rates. Instead, the TLC is choosing the adopt an industry-wide utilization rate that does not hold bases accountable for keeping cars full with paying passengers.”

    #USA #New_York #Uber #Mindestlohn

  • Decentralised Applications and the problem with adoption

    Much has been said about the state of decentralised applications (dApps) recently. Most has been negative, stating that #dapps have, in general, not lived up to the promises from the halcyon visions outlaid in ICO whitepapers. Have these commentators been too quick to judge? Or, are they right and dApps are but a fickle endeavour? Well the truth, as usual, probably rests somewhere between both camps. Perhaps, at this point in time, we should remember the old adage that Constantinople wasn’t build in a day…It took AirBnb almost four years to crack 1m users, Uber similar and the digital freelancing platform UpWork took nearly twenty years, three mergers and tens of millions of dollars to get where it is today. Most of these dApps have only been around for less than a year.Also, although a (...)

    #canya #cryptocurrency #blockchain #application

  • Lyft Is Not Your Friend


    Lyft is the latest brand trying to build market share by posing as a “progressive” corporation. But the fight can’t be good corporations against bad ones — it’s working people against capitalism.
    In early 2017, liberals hit on a new strategy to resist the nascent Trump administration: #DeleteUber.

    It started when New York City’s taxi drivers refused to service JFK airport to protest Trump’s travel ban targeting Muslim-majority countries, and Uber was spotted leveraging the ensuing crisis for profit. Then Uber CEO Travis Kalanick came under fire for accepting an appointment to Trump’s economic advisory council. He announced his resignation from the council, but only weeks later a video leaked of Kalanick reprimanding a driver for his company.

    Amid various ensuing scandals, Kalanick stepped down as CEO of Uber, but by then millions of consumers had turned on the brand in protest, deleting the Uber app from their phone and opting instead for the rideshare giant’s rival Lyft.

    Lyft leaned in, eagerly branding itself as the progressive alternative to Uber by pledging a $1 million donation to the ACLU and trotting out celebrities to promote it as a company committed to “doing things for the right reasons.” Lyft, of course, operates on the same labor model as Uber — its drivers are not employees but independent contractors, and are therefore denied all the benefits and protections that workers receive under more ideal circumstances. Nevertheless, a new refrain rang out across liberaldom: “I don’t use Uber, I use Lyft.”

    What socialists understand that liberals don’t is that brands are corporate enterprises, and corporate enterprises are fundamentally motivated by the pursuit of profit — even in their ostentatious acts of charity and wokeness.

    Three surefire ways to maximize profit are: suppressing labor costs by paying workers as little as you can get away with, lobbying the state for deregulation and lower taxes, and opening new markets by finding new things to commodify and sell. Businesses will always pursue these avenues of profit maximization where they can. It’s not a matter of ethics but of market discipline: if they don’t, they run the risk of losing out to the competition and eventually capsizing.

    Sometimes corporations do things for publicity that make it seem like their interests are not fundamentally misaligned with those of the working-class majority, who rely on decent wages and well-funded public services. But those efforts are meant to sustain public confidence in a given corporation’s brand, which is occasionally necessary for keeping up profits, as Uber’s losses in 2017 demonstrate. When corporate profits come into direct conflict with active measures to improve people’s wellbeing, corporations will always select the former. Case in point: Lyft just donated $100k to the campaign against a ballot measure that would create a tax fund to house the homeless in San Francisco, where the company is based.

    Why did the progressive alternative to Uber do this? Well, because the company doesn’t want to pay higher taxes. Because high taxes imperil profits, and profits are the point. Another likely rationale is to build stronger bonds with pro-business advocacy groups in San Francisco, so that the company will have allies if the city decides to implement regulations against ride-sharing services, which is rumored to be a possibility.

    Lyft has already mastered the art of suppressing labor costs and opening new markets. Next on the wish list, low taxes and deregulation. It’s pretty formulaic when you get down to it.

    San Francisco is home to an estimated 7,500 homeless people. Proposition C would tap the large corporations that benefit from the city’s public infrastructure to double the city’s homelessness budget in an attempt to resolve the crisis. The corporations opposing Proposition C say that the move would imperil jobs. This is not an analysis, it’s a threat. What they’re saying is that if the city reaches too far into their pockets, they’ll take their business elsewhere, draining the region of jobs and revenue as punishment for government overreach. It’s a mobster’s insinuation: Nice economy, shame if something happened to it. Meanwhile thousands of people sleep in the streets, even though the money to shelter them is within the city’s borders.

    Of course, in every struggle over taxes and industry regulation there may be a few canny corporate outliers looking to ingratiate their brand to the public by bucking the trend. In the case of Proposition C, it’s Salesforce, whose CEO Marc Benioff has made a public display of support for the ballot measure. But before you rush to praise Benioff, consider that only two months ago he lauded Trump’s tax cuts for fueling “aggressive spending” and injecting life into the economy.

    You could spend your life as an engaged consumer hopping from brand to brand, as liberals often do, pledging allegiance to this one and protesting that one to the beat of the new cycle drum. You could delete Lyft from your phone the same way you did with Uber, and find another rideshare app that you deem more ethical, until that one inevitably disappoints you too.

    Or you could press pause, stop scrambling for some superior consumption choice to ease your conscience, and entertain the socialist notion that deep down all corporations are objectively the same. They all exist to maximize return on investment for the people who own them. They are all in competition with each other to plunder our commons most effectively, with the lowest overhead, which means compensating the least for employees’ work. And when the rubber meets the road, they will all prioritize private profits over the wellbeing of those who own no productive assets, which is the vast majority of the people on the planet. They will demonstrate these priorities on a case-by-case basis, and on a massive global scale so long as capitalism prevails.

    “We’re woke,” said Lyft CEO John Zimmerman at the height of the Uber scandal. It was horseshit — it always is. And until liberals stop believing than any brand can be truly “woke,” or can offer a genuine alternative to the predatory behavior they observe in other “unwoke” brands, they’ll be unable to mount a meaningful resistance to anything.

    Whether we want to ensure clean drinking water for the residents of Flint or to shelter the homeless of San Francisco, we have to draw clear battle lines that are up to the challenge. The fight can’t be good corporations against bad corporations. It has to be working people against capitalism.

    #USA #transport #disruption #Lyft

  • Are STOs All They’re Cracked Up To Be?

    Imagine being able to own .1% of a Picasso or a fourth of an Uber cab that you split with three of your friends. Currently, such things would be burdensome at best or just nearly impossible. However, security tokens offerings (STOs) are providing a path to fractional ownership by enabling the tokenization of virtually anything we can think of. Such offerings have been sweeping the #cryptocurrency space, providing a regulated alternative to ICOs. Since security tokens are backed by underlying assets or profits, investors gain access to equity, voting rights, and dividends. In theory, this should allow anyone to invest into anything, opening the doors for unlimited opportunities never seen before. Yet in practice, there are quite a few obstacles one needs to be aware of before getting (...)

    #crypto #security-token-offering #sto-hype #sto

  • Uber fined £385,000 for data breach affecting millions of passengers

    Firm failed to tell 35 million users and 3.7 million drivers their data was hacked in 2016 Uber’s European operation has been fined £385,000 for a data breach that affected almost 3 million British users, the Information Commissioner’s Office has announced. In November 2016, attackers obtained credentials to access Uber’s cloud servers and downloaded 16 large files, including the records of 35 million users worldwide. The records included passengers’ full names, phone numbers, email addresses, (...)

    #Uber #données #procès #hacking #ICO-UK

  • High score, low pay : why the gig economy loves gamification | Business | The Guardian

    Using ratings, competitions and bonuses to incentivise workers isn’t new – but as I found when I became a Lyft driver, the gig economy is taking it to another level.

    Every week, it sends its drivers a personalised “Weekly Feedback Summary”. This includes passenger comments from the previous week’s rides and a freshly calculated driver rating. It also contains a bar graph showing how a driver’s current rating “stacks up” against previous weeks, and tells them whether they have been “flagged” for cleanliness, friendliness, navigation or safety.

    At first, I looked forward to my summaries; for the most part, they were a welcome boost to my self-esteem. My rating consistently fluctuated between 4.89 stars and 4.96 stars, and the comments said things like: “Good driver, positive attitude” and “Thanks for getting me to the airport on time!!” There was the occasional critique, such as “She weird”, or just “Attitude”, but overall, the comments served as a kind of positive reinforcement mechanism. I felt good knowing that I was helping people and that people liked me.

    But one week, after completing what felt like a million rides, I opened my feedback summary to discover that my rating had plummeted from a 4.91 (“Awesome”) to a 4.79 (“OK”), without comment. Stunned, I combed through my ride history trying to recall any unusual interactions or disgruntled passengers. Nothing. What happened? What did I do? I felt sick to my stomach.

    Because driver ratings are calculated using your last 100 passenger reviews, one logical solution is to crowd out the old, bad ratings with new, presumably better ratings as fast as humanly possible. And that is exactly what I did.

    In a certain sense, Kalanick is right. Unlike employees in a spatially fixed worksite (the factory, the office, the distribution centre), rideshare drivers are technically free to choose when they work, where they work and for how long. They are liberated from the constraining rhythms of conventional employment or shift work. But that apparent freedom poses a unique challenge to the platforms’ need to provide reliable, “on demand” service to their riders – and so a driver’s freedom has to be aggressively, if subtly, managed. One of the main ways these companies have sought to do this is through the use of gamification.

    Simply defined, gamification is the use of game elements – point-scoring, levels, competition with others, measurable evidence of accomplishment, ratings and rules of play – in non-game contexts. Games deliver an instantaneous, visceral experience of success and reward, and they are increasingly used in the workplace to promote emotional engagement with the work process, to increase workers’ psychological investment in completing otherwise uninspiring tasks, and to influence, or “nudge”, workers’ behaviour. This is what my weekly feedback summary, my starred ratings and other gamified features of the Lyft app did.

    There is a growing body of evidence to suggest that gamifying business operations has real, quantifiable effects. Target, the US-based retail giant, reports that gamifying its in-store checkout process has resulted in lower customer wait times and shorter lines. During checkout, a cashier’s screen flashes green if items are scanned at an “optimum rate”. If the cashier goes too slowly, the screen flashes red. Scores are logged and cashiers are expected to maintain an 88% green rating. In online communities for Target employees, cashiers compare scores, share techniques, and bemoan the game’s most challenging obstacles.

    But colour-coding checkout screens is a pretty rudimental kind of gamification. In the world of ride-hailing work, where almost the entirety of one’s activity is prompted and guided by screen – and where everything can be measured, logged and analysed – there are few limitations on what can be gamified.

    Every Sunday morning, I receive an algorithmically generated “challenge” from Lyft that goes something like this: “Complete 34 rides between the hours of 5am on Monday and 5am on Sunday to receive a $63 bonus.” I scroll down, concerned about the declining value of my bonuses, which once hovered around $100-$220 per week, but have now dropped to less than half that.

    “Click here to accept this challenge.” I tap the screen to accept. Now, whenever I log into driver mode, a stat meter will appear showing my progress: only 21 more rides before I hit my first bonus.

    In addition to enticing drivers to show up when and where demand hits, one of the main goals of this gamification is worker retention. According to Uber, 50% of drivers stop using the application within their first two months, and a recent report from the Institute of Transportation Studies at the University of California in Davis suggests that just 4% of ride-hail drivers make it past their first year.

    Before Lyft rolled out weekly ride challenges, there was the “Power Driver Bonus”, a weekly challenge that required drivers to complete a set number of regular rides. I sometimes worked more than 50 hours per week trying to secure my PDB, which often meant driving in unsafe conditions, at irregular hours and accepting nearly every ride request, including those that felt potentially dangerous (I am thinking specifically of an extremely drunk and visibly agitated late-night passenger).

    Of course, this was largely motivated by a real need for a boost in my weekly earnings. But, in addition to a hope that I would somehow transcend Lyft’s crappy economics, the intensity with which I pursued my PDBs was also the result of what Burawoy observed four decades ago: a bizarre desire to beat the game.

    Former Google “design ethicist” Tristan Harris has also described how the “pull-to-refresh” mechanism used in most social media feeds mimics the clever architecture of a slot machine: users never know when they are going to experience gratification – a dozen new likes or retweets – but they know that gratification will eventually come. This unpredictability is addictive: behavioural psychologists have long understood that gambling uses variable reinforcement schedules – unpredictable intervals of uncertainty, anticipation and feedback – to condition players into playing just one more round.

    It is not uncommon to hear ride-hailing drivers compare even the mundane act of operating their vehicles to the immersive and addictive experience of playing a video game or a slot machine. In an article published by the Financial Times, long-time driver Herb Croakley put it perfectly: “It gets to a point where the app sort of takes over your motor functions in a way. It becomes almost like a hypnotic experience. You can talk to drivers and you’ll hear them say things like, I just drove a bunch of Uber pools for two hours, I probably picked up 30–40 people and I have no idea where I went. In that state, they are literally just listening to the sounds [of the driver’s apps]. Stopping when they said stop, pick up when they say pick up, turn when they say turn. You get into a rhythm of that, and you begin to feel almost like an android.”

    In their foundational text Algorithmic Labor and Information Asymmetries: A Case Study of Uber’s Drivers, Alex Rosenblat and Luke Stark write: “Uber’s self-proclaimed role as a connective intermediary belies the important employment structures and hierarchies that emerge through its software and interface design.” “Algorithmic management” is the term Rosenblat and Stark use to describe the mechanisms through which Uber and Lyft drivers are directed. To be clear, there is no singular algorithm. Rather, there are a number of algorithms operating and interacting with one another at any given moment. Taken together, they produce a seamless system of automatic decision-making that requires very little human intervention.

    For many on-demand platforms, algorithmic management has completely replaced the decision-making roles previously occupied by shift supervisors, foremen and middle- to upper- level management. Uber actually refers to its algorithms as “decision engines”. These “decision engines” track, log and crunch millions of metrics every day, from ride frequency to the harshness with which individual drivers brake. It then uses these analytics to deliver gamified prompts perfectly matched to drivers’ data profiles.

    To increase the prospect of surge pricing, drivers in online forums regularly propose deliberate, coordinated, mass “log-offs” with the expectation that a sudden drop in available drivers will “trick” the algorithm into generating higher surges. I have never seen one work, but the authors of a recently published paper say that mass log-offs are occasionally successful.

    Viewed from another angle, though, mass log-offs can be understood as good, old-fashioned work stoppages. The temporary and purposeful cessation of work as a form of protest is the core of strike action, and remains the sharpest weapon workers have to fight exploitation. But the ability to log-off en masse has not assumed a particularly emancipatory function.

    After weeks of driving like a maniac in order to restore my higher-than-average driver rating, I managed to raise it back up to a 4.93. Although it felt great, it is almost shameful and astonishing to admit that one’s rating, so long as it stays above 4.6, has no actual bearing on anything other than your sense of self-worth. You do not receive a weekly bonus for being a highly rated driver. Your rate of pay does not increase for being a highly rated driver. In fact, I was losing money trying to flatter customers with candy and keep my car scrupulously clean. And yet, I wanted to be a highly rated driver.
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    And this is the thing that is so brilliant and awful about the gamification of Lyft and Uber: it preys on our desire to be of service, to be liked, to be good. On weeks that I am rated highly, I am more motivated to drive. On weeks that I am rated poorly, I am more motivated to drive. It works on me, even though I know better. To date, I have completed more than 2,200 rides.

    #Lyft #Uber #Travail #Psychologie_comportementale #Gamification #Néo_management #Lutte_des_classes

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