quotage: "This is the real ethical dimension of artificial intelligence: it is not so much in the applications of the technology – many of which will be genuinely transformative and positive – it is in the thought processes that occurred before the coders were brought in, combined with the mindset and world views of the coders themselves. Microsoft’s Tay AI chatbot proved this last year beyond any doubt. Any tool released into the world by naïve, culturally unsophisticated researchers can be a destructive force." - Chris Middleton, WEF 2017 – Do ethics and AI use the same code?
myPOV: It was all hands on (virtual) decks as Stuart, Chris and Cath all covered the WEF (World Economic Forum) stream. Though financial markets clutch to cautious optimistism about recent elections (for now), the tone at WEF was more somber, raising questions on the surge of AI versus the prospect of digital refugees, alienated from so-called progress.
As Stuart reported in WEF 2017 – is the West’s ‘citizen mutiny’ a precursor to the ‘digital refugee’?, those concerns extended into tech, as per the views of Vishal Sikka (CEO Infosys) and Marc Benioff (CEO Salesforce). Chris - quoted above - pushed into the roots of AI ethics in WEF 2017 – Do ethics and AI use the same code?
Any wonder then, with this talk of programming inequality into our AI, and the fallout of digital refugees, that risk and security would dominate? See Stuart's WEF 2017 – the future of the digital economy is more security spend, and Cath's WEF 2017 – the changing nature of risk in a digital age, which explores the WEF's Global Risk Report 2017. I'd be doing a disservice if I portrayed this event as alarmist. The sense I get is not pessimism. It's a recognition that uncharted opportunities lie ahead, but only if we take the brutally sharp edge off the downside.diginomica four - my top four stories on diginomica this week
- How performance management led the HR way for Santa Fe -
Janine takes on the thorny problem of performance management in this two part use case (part two here). Terrific line: "The company needed to turn these pockets of excellence into consistent, standardized excellence across all regions." That's the quintessential enterprise dilemma eh?
- Scoring hoops for innovation – NBA lessons for business users - Martin's in my (basketball) wheelhouse now... As a fan of an NBA team that's infatuated with "advanced basketball analytics" - and the three point shot - I question whether advanced analytics are good for basketball. That's a dissection for another time. But: there is plenty to learn from the NBA's approach to media and fan engagement.
- Jellyfish Pictures deploys cloud and virtualization to magical effect - Jess gets the tech skinny from the CTO of Jellyfish, Europe’s first virtual visual effects studio. I'd joke that Jellyfish made workflow problems disappear, but that would be a cheap-@ss quip now wouldn't it?
- Paul Shetler’s perspective on UK, US and Australian government digital transformation - From diginomica/gov, here's a useful contrast between three different digital approaches. Got some spicy comments for our trouble.
Vendor analysis, diginomica style. Here's my three top choices from our vendor coverage:
- Mark Hurd, co-CEO Oracle, on Brexit, Trump and digital government - Den's stint at the Oracle Cloud Summit sparked this take from Hurd on the issues du jour: "Hurd’s answer is interesting because, for the first time, we are hearing an insight into the way government spending works from the supply side. Oracle is important in this context as one of the largest suppliers to both the UK and US governments so if they are experiencing a degree of frustration then you can be sure that is the tip of the iceberg. For ourselves, we see plenty of frustration among those who are endeavoring to bring efficiencies and those who are trying to meet those needs."
- How Walmart honed its people analytics to deliver business value - Phil adds context from a prior event to a big HCM story: "Winding forward to the present day, it provides important context for understanding the decision to sign up for Workday’s HCM platform with its built-in analytics capabilities. With a global team of 60-plus solely dedicated to delivering people analytics — and to proving its business value — Walmart has already seen ample evidence of the value people analytics can deliver in a retail business." Plus the killer quote from inside: "The biggest threat I see to Walmart is groupthink."
- This services firm retains staff by tracking their daily happiness - Michelle Swan makes her diginomica debut (welcome Michelle!) with this cool piece on Traction on Demand, which runs on the Salesforce platform. Not your typical IT shop: "No matter what you call it, the company’s approach seems to be working — with a 573% leap in revenue growth over the last three years, an industry-low 5% employee turnover rate, and a long list of HR and Best Places to Work awards."
A few more vendor picks, without the quotables:
- DocuSign e-signs new CEO, who says it’s ‘IPO-ready’ - Phil
- And finally, SAP Business ByDesign is relevant to SME - Brian
- SAP’s Leonardo points towards Applied Data Science as a Service - Martin
- Salesforce Commerce Cloud CEO at NRF – 75 percent of retailers are “ill-prepared” for the omni-channel - yours truly, live from NRF. Also check my use case, Vibram: B2C on the Salesforce platform changed our business – live from NRF ’17.
Jon's grab bag - Like the rest of the U.S. we went
orange Trumpian last week. Stuart filed the WEF-angled What impact will Trump’s climate change views have on tech industry Green progress? Den did the informed speculation thing in Trump healthcare plans could be a winner – a tech nightmare and bonanza. and came out sounding dumbfoundingly refreshingly optimistic.
Kurt dug further into health care disruption in Bringing Moore’s Law to US healthcare – huge IT opportunities, using electronic records and analytics as proof points. Of the bureaucratic boot anchor on health change, Kurt writes: "The proximate catalyst for change is a new administration in Washington unafraid to gore political sacred cows." As someone who did not vote for Trump, that is a best case scenario I can root for. Finally, for you digital marketers out there, Barb just wrapped a worthy three-parter, Account-based marketing III – metrics, post-acquisition support and relationships.
Best of the restThere are really no data scientists in the wild! by Vijay Vijayasankar
quotage: "There are statisticians, there are mathematicians, there are engineers , there are machine learning programmers, and there are many other types of experts out there – but there are really no data scientists out there in the wild ! What exists are data science teams and many are generally awesome . That is my conclusion after trying really hard to become a data scientist myself over the last few months."
punked teased inflamed data scientists the world over with this efficient evisceration. It's easy to see how they would be ticked off; Vijayasankar is milking a pretty sacred cow. But having talked with Vijayasankar - who I know well - I know he does not want data scientists to stop aspiring for excellence. Nor does he want to minimize their contributions. He wants - a spirited debate.
Vijayasankar is saying two things: first, there is as much "art" to being a data scientist as "science." I suspect most data scientists would agree. Second - and here I agree with Vijayasankar completely - he's saying successful data science projects are a team sport. That's true for almost any IT discipline but it's particularly true for data scientists, where the skill set requires a convergence of sophisticated know-how, from R to Hadoop to stats to predictive.
Data scientists shouldn't breath easy yet. Vijayasankar could write whole posts on why you must have industry know-how, and the client-facing savvy to talk numbers in a customer context. If a few get near the total package, they are rock stars. "Only hire rock stars" is the equivalent of telling companies to put their data science projects on hold. The alternative? A bit of humility, and a well-balanced data science team where everyone knows their role. I'm looking forward to hearing a detailed counter-argument. Meantime, here's my prior view on data-science-as-team-sport.
- Briefing Notes: Oracle IaaS - Krishnan Subramanian has been depriving us of his cloud analysis for a while, but he's back - at least this time, with a probing look at Oracle's ambitious IaaS play.
- SAP’s S/4 HANA: Looking Good, Trying to Look Better - Joshua Greenbaum assesses S/4HANA from the vantage point of ASUG's most recent member survey (ASUG is SAP's North American User Group).
- Nate Silver's Lessons for Big Data from the Unpredicted Trump Victory - Nate Silver's running too many victory laps for what I see as his own mediocre showing, but his insights are instructive nonetheless.
- Customer service takes a turn - Wherein a survey is expertly dissected.
- Make Operations Your Secret Weapon - Here’s How - When was the last time you read a terrific, long-form piece on being a swell Chief Operating Officer?
- 3 Lessons From The Yahoo Breach - Take your security vitamins please.
- Tesla Cleared In Fatal Autopilot Crash Investigation - No surprises here, and yes, I'm including the warning to Tesla's misleading marketing.
- Virginia Tech Fights Zika With High-Performance Prediction - Your feel-good-about-tech story #1.
- How to Control a Robotic Arm with Your Mind - feel-good-story number two. No crusty curmudgeons in sight!
The biggest barrier to Windows 10 success is still Windows 7? As the conflicted owner of a Windows 10 machine, I haven't found a single thing I like better about Windows 10. Found plenty of crud that's worse, including automatic "updates" aka testware that can't be disabled. Why do so many tech companies take a big dump on what's working?So
This was fun:
20 bullsh*t buzzwords that should be banned from tech forever https://t.co/8GKrmqsdrT -> where is cadence? Nice to see "low hanging fruit"
— Jon Reed (@jonerp) January 23, 2017
@jonerp He missed seamless, as in "seamless integration." And proven, as in "proven methodology." And "leading," and in "leading provider."
— Frank Scavo (@fscavo) January 23, 2017
Yep - he also missed imagine, as in "re-imagine," and practice, as in "best practice" (yuck). But it's a far above average skewering. Finally, this lazy blog post, Robots are Coming for Half Your Jobs, has been bugging me. This strikes me as less a blog post, and more of a half-finished sketch on the back of a napkin. a few nits you'd toss into Evernote. I think this a critique of the Trump administration's woefully inadequate public positions on robotics and automation, but the word "withering" doesn't come to mind...
The post ends abruptly - I guess the author, re/code's Peter Kafka, ran out of napkin. Kafka refers to a "new" McKinsey report, with no link. The data appears to be from a flawed/interesting report from last July. There are ingredients for a blog post here. I guess that's what it is, a recipe for something better. Let's hope the author puts it back in the oven. Over to you, Clive.
Updated 5pm ET Tuesday the 24th, with a couple small clarifications to the data science commentary.