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Increasing Customer Loyalty

Increasing Customer Loyalty

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Increasing customer loyalty is a very important aspect of business today. There are too many choices for customers to go elsewhere on a whim. This is not to say that a company shouldn’t continue to acquire new customers, but the loyal customers are the ones that will name drop you in conversations. They will recommend you to their friends and family. They will broadcast your message on social channels and in emails.

But how do you keep them? How do you keep them around? Simply put, treat these customers as you would want to be treated. We’re taught this easy to remember rule as kids and it applies here. Even now, as you may be providing the service and/or products to customers, you yourself are a customer to other businesses as well. How do you like to be treated when you go to your favorite store or restaurant? Is it because of the way you’re treated from the time you walk in the door?
Business owners should be even more prepared and alert to know what the preferences and wants of customers on both sides of the counter. You provide the resources that customers depend on you to share so that their experience is a win from start-to-finish. This can lay the foundation on which loyalty can be built upon.

Your employees that are front-facing are the faces of the company. They are on the frontlines, they hear the complaints, they see buying trends and can have a direct impact on whether or not customers stay loyal and a positive buying experience. Empower your employees by opening lines of conversations with them. Ask them what they are hearing or what they are seeing. Customers will express their concerns or whether they like a change in pricing, products, services, etc.

An easy way to open these lines of communication is to have regular staff meetings and listening to them. Being open to change and listening to the dialogue can tell you more than almost any other type of data because it is coming straight from the customer.

Since communication has been mentioned, remember that customers want that communication, they want to know what is happening with their favorite companies because it impacts them directly. It creates a sense of belonging to a community of peers and like-minded people.

Customers are savvy. There isn’t an ignorant consumer anymore waiting for a salesperson to take advantage of them. They do their research online. They may even go to a local store to actually touch the product and then go online and purchase because the prices are cheaper.

But they’ll frequent the businesses they’re familiar with because you offer expertise in the product they are seeking. They may know about the product or service, but because you have chosen to open a business in that vertical, you are the expert in their opinion.

Share this knowledge. An easy way to do this is with a company blog or sharing of information through social media channels. Build a database of knowledge. Share on a FAQ page. Loyal customers can even be employed to share this information. Offer simple rewards for this. A logo cap or t-shirt can do wonders for customer loyalty.

There are a lot of companies that make this a priority. They have become totally transparent to the detriment of possibly losing business. They share company policies, their purchasing and supply choices and even manufacturing information. The ice cream company, Ben and Jerry’s, has adapted this practice. They share information on where and how their dairy products are produced. A factory tour shows the commitment to the environment and production practices to anyone that attends. The only item that they won’t share is the recipe for their ice cream flavors sadly.

In exchange for this information, you can use the opportunity to ask your customers what they think of the company. Ask how the company can improve the buying experience. While it may be hard to ask these questions in person or on a phone call, most of the time, an email or online survey will work. If you are not receiving the amount of feedback you seek, offer the logo cap or t-shirt as a reward or a discount on future purchases.

Rewarding customers have become a regular occurrence for most companies today. When a customer is at the POS (Point of Sale), the clerk will offer a discount for applying for a credit card usually. Some companies offer a points system with a reward after a certain amount of accrued points. For example, Starbucks will offer free drinks after an amount of purchases are met.

Customers will also become loyal to companies that share the same values and they will return for the simplest of reasons; be loyal to them.

The post Increasing Customer Loyalty appeared first on Sensei Marketing.

Next-Generation Customer Experience Chief Customer Officer

SuperNova Award Deadline Extended to August 11

SuperNova Award Deadline Extended to August 11

New deadline August 11, 2017

You now have a few more days to complete your SuperNova Award application! The new deadline to apply for the SuperNova Awards is August 11, 2017.

Apply here

In its seventh year, the Constellation SuperNova Awards will recognize ten individuals who demonstrate true leadership in digital business through their application of new and emerging technologies.

SuperNova Awards for Leaders in Disruptive Tech

We’re searching for leaders and teams who used disruptive technolgies to transform their organizations. 

Revised Timeline

  • August 4, 2017 August 11, 2017 last day for submissions.
  • September 7, 2017 finalists announced and invited to Connected Enterprise.
  • September 12, 2017 voting opens to the public
  • September 21, 2017 polls close
  • October 27, 2017 Winners announced, SuperNova Awards Gala Dinner at Connected Enterprise 

How to Apply for a SuperNova Award:

  1. Download the SuperNova Award application. Click here. 
  2. Submit your application via webform by August 11, 2017. Submit applications here.  

Tips & FAQ

  • Nominate your customers - the Awards recognize the leadership of end users of technology. 
  • Agencies representing technology companies - nominate the customers of technology companies. We want case studies about how customers are using technology. 
  • Make a strong case - tell us about how the nominee won buy-in, led the implementation, drove adoption, and achieved positive ROI
  • Provide strong metrics - judges want proof that the project was successful. Provide before and after implementation results. 
  • Results v. Metrics - results are a verbal explanation of how your project created a disruption; metrics are numbers that provide evidence of your results. 
  • "Disruptiveness" may mean creating an internal or external disruption OR using disruptive technology to change business models
  • Ensure your application is not bound by an NDA - All applications should be web ready. Do not include any information that can not be made public. 

More resources 

About the 2017 SuperNova Awards

Last year's winners

Questions? email [email protected]

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Google's Shopper-Tracking Program Comes Under Fire from Privacy Advocates

Google's Shopper-Tracking Program Comes Under Fire from Privacy Advocates

Constellation Insights

Google is coming under fire from the watchdog group Electronic Privacy Information Center, which has filed a complaint asking the Federal Trade Commission to probe a new Google advertising technology that matches customers' online activities with things they buy in retail stores. Here are the key details from a report in the Washington Post:

The legal complaint from [EPIC] alleges that Google is newly gaining access to a trove of highly sensitive information -- the credit and debit card purchase records of the majority of U.S. consumers -- without revealing how they got the information or giving consumers meaningful ways to opt out. Moreover, the group claims that the search giant is relying on a secretive technical method to protect the data -- a method that should be audited by outsiders and is likely vulnerable to hacks or other data breaches.

Using the debit card information, Google's algorithms can match transactions to users on its various services, albeit in anonymized fashion. Google is defending its methods as common and says it has developed encryption methods that keep user data safe and private. But EPIC says the government needs to review Google's practices for itself, the Post reported.

Analysis: Sunshine needed

As the saying goes, what's done in the dark will eventually come out into the light. But Google shouldn't wait to be compelled to provide information about how the advertising program works under the hood, says Constellation Research VP and principal analyst Steve Wilson.

"They really should submit to an independent security review, so we can all be confident about the privacy promise," Wilson says. "The view can be confidential to protect Google's trade secrets but it has to be independent."

Another important aspect of transparency are user terms and conditions. Google seems to be implying that shoppers have consented to the reuse of their payment data, but many customers click OK on such agreements without really comprehending what they mean, he adds. Ts&Cs for other consumer services, such as credit cards or insurance, have standardized "plain language" contracts meant to protect people against fine print. "We need this type of transparency in the data economy," Wilson says.

Companies like to say they offer good value in exchange for customers' data and that in return customers enjoy the free services. "I reckon that's a dubious proposition but even if it's true, then why are all the privacy settings 'opt out?'," Wilson says. "By default, data is reused and resold far and wide unless customers find the opt-out settings. If the data-for-service bargain is as good as the data magnates say, then I'd expect them to have faith that customers would consciously opt-in."

To that end, EPIC contends that the opt-out settings for Google's products are too complicated and unclear.

"Consumer advocates like EPIC are rightly worried about the assymetry in these arrangements, as data collection methods and systems are put together by some of the most clever people in business," Wilson adds. "They know far more about data practices than the humble customer ever will. So exploitation is simply inevitable."

 

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Digital Transformation Digest: Facebook, LogMeIn Nab AI Startups, Bitcoin's Big Split, and More

Digital Transformation Digest: Facebook, LogMeIn Nab AI Startups, Bitcoin's Big Split, and More

Constellation Insights

The AI arms race continues: AI and machine learning startups have been popping up like mad in recent times, and are being acquired just as quickly. This week, Facebook and SaaS application vendor LogMeIn continued the trend, buying Ozlo and Nanorep, respectively.

Ozlo's capabilities will be rolled into Facebook Messenger to help it build "compelling experiences" that are "powered by artificial intelligence and machine learning," Facebook said. For its part, Ozlo says it has built a knowledge graph that contains more than 2 billion entities, making its technology able to "understand real-world nuances." Translation: Facebook wants to improve its chatbots level of understanding and interaction with users. Terms of the Ozlo deal weren't disclosed.

Meanwhile, LogMeIn is paying about $50 million for Nanorep, an Israeli startup focused on customer self-service, chatbot and virtual assistant technology. The deal will complement LogMeIn's recently launched customer engagement platform, Bold360.

POV: The flurry of AI acquisitions is no surprise given the energy in the market, as larger vendors scramble to get their AI strategies in shape. It's telling that even a company with as many resources as Facebook is going down this path, suggesting that acquiring AI talent as much as technology is a key driver for these deals. 

Bitcoin's big split: The world's leading cryptocurrency was forked on Tuesday by a minority group of developers backing a new iteration, which will be called Bitcoin Cash. The split comes after a couple of years of debate in the Bitcoin community over the cryptocurrency's blockchain architecture, which at present allows fewer than 10 transactions per second. Bitcoin Cash's approach will increase the currency's scalability.

The new currency faces some challenges, chief among them the fact that only some Bitcoin exchanges will support it for now. It also won't be able to take advantage of the services ecosystem built up around Bitcoin. In turn, the currency could cause market confusion among would-be investors, as well as cause headaches for companies building their businesses on Bitcoin.

POV: It will be some time before Bitcoin Cash's success or failure can be measured, as well as its impact on Bitcoin. On a philosophical level, there are strong arguments for and against it from an open-source software perspective. In the first case, the ability to fork code is a bedrock tenet of open source. But as one critic points out, Bitcoin Cash's technical approach could make its blockchain too large for smaller organizations to store in its entirety, leaving more control in the hands of fewer players—the exact opposite of the decentralized structure touted by Bitcoin from the beginning.

Malware via machine learning: The prospect of AI becoming a threat to humans is a popular topic, and new software created by security vendor Endgame will do little to quell that discussion. Endgame used the AI framework provided by Elon Musk-backed nonprofit OpenAI to generate malware that can defeat antivirus software, as the Register reports:

In a keynote demonstration at the DEF CON hacking convention Hyrum Anderson, technical director of data science at security shop Endgame ... cited research by Google and others to show how changing just a few pixels in an image can cause classification software to mistake a bus for an ostrich.

“All machine learning models have blind spots,” he said. “Depending on how much knowledge a hacker has they can be convenient to exploit.”

So the team built a fairly simple mechanism to develop weaponised code by making very small changes to malware and firing these variants at an antivirus file scanner. By monitoring the response from the engine they were able to make lots of tiny tweaks that proved very effective at crafting software nasties that could evade security sensors.

Endgame's software managed to defeat the security software 16 percent of the time, according to the Register.

POV: Security vendors already widely use machine learning for defensive means, and tools such as Endgame's should prove useful for penetration testing. And Endgame wasn't the only vendor at DEF CON demonstrating an AI-based hacking tool. Security consultancy Bishop Fox showcased DeepHack, which uses AI to break into web applications. Here's how it describes the approach:

DeepHack works the following way: Neural networks used in reinforcement learning excel at finding solutions to games. By describing a problem as a "game" with winners, losers, points, objectives, and actions, a neural network can be trained to be proficient at "playing" it. The AI is rewarded every time it sends a request to gain new information about the target system, thereby discovering what types of requests lead to that information.

While Endgame and Bishop Fox's intentions are benevolent, it's an open question as to how much AI becomes a tool for malicious hackers going forward.

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Summer 2017 News Analysis - Microsoft Makes Azure Stack Available

Summer 2017 News Analysis - Microsoft Makes Azure Stack Available

What’s the news: Azure Stack – announced a little more than two years ago is Microsoft’s on premise version of Azure (with some reduced / missing capabilities to the cloud version). Originally slated to run on Microsoft hardware and available last summer, the product suite is now available for partners to certify. And partners (the usual suspects) are in line to certifiy their hardware asap.
 

Why it matters: Despite the trend to cloud there are still many enterprises that have to operate enterprise automation on premises. Look at the number of SAP customers opting to run S/4HANA on premises. Microsoft now offers a path for them to run Azure similar / identical products – and build and move applications and load to an Azure like on premises stack – with the option to move it later. And there are plenty of motivated hardware vendors that want to sell more servers to customers for their local data centers (Cisco, Dell, HP etc etc.)
 
The intro slide of Azure Stack from Build 2015


MyPOV: Good to see more on-premise options coming, a key move for Microsoft to help customers stay on Microsoft and get future proof. How well the partner approach will work for this – remains to be seen. But Microsoft has a successful track decade spanning record to partner with hardware vendors. The partner approach differs from Oracle – that provides all themselves, but as well with the on premises vs cloud choice. With enterprises getting same / similar options from trusted vendors (don’t forget IBM here, too) – they will look at these offerings more seriously.

CxO Advice: If you are a Microsoft shop with on premises requirements (data privacy, residency, performance, data center availability, legacy loads) this a key announcement. It’s must prototype and pilot territory. Don’t wait for your favorite hardware vendor for this, they will all come along in a few months, when a positive pilot leads to a production decision. Azure stack as a pilot on any test can have the bonus as a lock-in avoidance as well as a commercial argument. In general CIOs and CTOs need to see that not all loads must go to the cloud, but we still recommend the cloud from an innovation speed and elasticity for most enterprise scenarios.
 
 
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McKinsey’s State Of Machine Learning And AI, 2017

McKinsey’s State Of Machine Learning And AI, 2017

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  • Tech giants including Baidu and Google spent between $20B to $30B on AI in 2016, with 90% of this spent on R&D and deployment, and 10% on AI acquisitions.
  • Artificial Intelligence (AI) investment has turned into a race for patents and intellectual property (IP) among the world’s leading tech companies.
  • U.S.-based companies absorbed 66% of all AI investments in 2016. China was second with 17% and growing fast.
  • By providing better search results, Netflix estimates that it is avoiding canceled subscriptions that would reduce its revenue by $1B annually.

These and other findings are from the McKinsey Global Institute Study, and discussion paper, Artificial Intelligence, The Next Digital Frontier (80 pp., PDF, free, no opt-in) published last month. McKinsey Global Institute published an article summarizing the findings titled   How Artificial Intelligence Can Deliver Real Value To Companies. McKinsey interviewed more than 3,000 senior executives on the use of AI technologies, their companies’ prospects for further deployment, and AI’s impact on markets, governments, and individuals.  McKinsey Analytics was also utilized in the development of this study and discussion paper.

Key takeaways from the study include the following:

  • Tech giants including Baidu and Google spent between $20B to $30B on AI in 2016, with 90% of this spent on R&D and deployment, and 10% on AI acquisitions. The current rate of AI investment is 3X the external investment growth since 2013. McKinsey found that 20% of AI-aware firms are early adopters, concentrated in the high-tech/telecom, automotive/assembly and financial services industries. The graphic below illustrates the trends the study team found during their analysis.

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  • AI is turning into a race for patents and intellectual property (IP) among the world’s leading tech companies. McKinsey found that only a small percentage (up to 9%) of Venture Capital (VC), Private Equity (PE), and other external funding. Of all categories that have publically available data, M&A grew the fastest between 2013 And 2016 (85%).The report cites many examples of internal development including Amazon’s investments in robotics and speech recognition, and Salesforce on virtual agents and machine learning. BMW, Tesla, and Toyota lead auto manufacturers in their investments in robotics and machine learning for use in driverless cars. Toyota is planning to invest $1B in establishing a new research institute devoted to AI for robotics and driverless vehicles.

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  • McKinsey estimates that total annual external investment in AI was between $8B to $12B in 2016, with machine learning attracting nearly 60% of that investment. Robotics and speech recognition are two of the most popular investment areas. Investors are most favoring machine learning startups due to quickness code-based start-ups have at scaling up to include new features fast. Software-based machine learning startups are preferred over their more cost-intensive machine-based robotics counterparts that often don’t have their software counterparts do. As a result of these factors and more, Corporate M&A is soaring in this area with the Compound Annual Growth Rate (CAGR) reaching approximately 80% from 20-13 to 2016. The following graphic illustrates the distribution of external investments by category from the study.

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  • High tech, telecom, and financial services are the leading early adopters of machine learning and AI. These industries are known for their willingness to invest in new technologies to gain competitive and internal process efficiencies. Many start-ups have also had their start by concentrating on the digital challenges of this industries as well. The\ MGI Digitization Index is a GDP-weighted average of Europe and the United States. See Appendix B of the study for a full list of metrics and explanation of methodology. McKinsey also created an overall AI index shown in the first column below that compares key performance indicators (KPIs) across assets, usage, and labor where AI could contribute. The following is a heat map showing the relative level of AI adoption by industry and key area of asset, usage, and labor category.

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  • McKinsey predicts High Tech, Communications, and Financial Services will be the leading industries to adopt AI in the next three years. The competition for patents and intellectual property (IP) in these three industries is accelerating. Devices, products and services available now and on the roadmaps of leading tech companies will over time reveal the level of innovative activity going on in their R&D labs today. In financial services, for example, there are clear benefits from improved accuracy and speed in AI-optimized fraud-detection systems, forecast to be a $3B market in 2020. The following graphic provides an overview of sectors or industries leading in AI addition today and who intend to grow their investments the most in the next three years.

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  • Healthcare, financial services, and professional services are seeing the greatest increase in their profit margins as a result of AI adoption. McKinsey found that companies who benefit from senior management support for AI initiatives have invested in infrastructure to support its scale and have clear business goals achieve 3 to 15% percentage point higher profit margin. Of the over 3,000 business leaders who were interviewed as part of the survey, the majority expect margins to increase by up to 5% points in the next year.

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  • Amazon has achieved impressive results from its $775 million acquisition of Kiva, a robotics company that automates picking and packing according to the McKinsey study. “Click to ship” cycle time, which ranged from 60 to 75 minutes with humans, fell to 15 minutes with Kiva, while inventory capacity increased by 50%. Operating costs fell an estimated 20%, giving a return of close to 40% on the original investment
  • Netflix has also achieved impressive results from the algorithm it uses to personalize recommendations to its 100 million subscribers worldwide. Netflix found that customers, on average, give up 90 seconds after searching for a movie. By improving search results, Netflix projects that they have avoided canceled subscriptions that would reduce its revenue by $1B annually.
Data to Decisions

Digital Transformation Digest: Samsung Eyes IoT Data Monetization, Google's Native Ad-Blocker Emerges, the Fight to Save Flash, and More

Digital Transformation Digest: Samsung Eyes IoT Data Monetization, Google's Native Ad-Blocker Emerges, the Fight to Save Flash, and More

Constellation Insights

Samsung wants to turn IoT data into money: In 2015, Samsung launched ARTIK, its entry into the IoT platform market. Now it is adding a layer to ARTIK that's aimed at helping IoT device makers generate revenue off the data they use. Here's the value proposition as stated in Samsung's announcement:

For device manufacturers, IoT shifts their operating model from selling hardware to selling hardware products connected to digital applications. Today, device manufacturers often have trouble recouping data costs associated with free applications and supporting an ecosystem of third-party devices, apps and services. Manufacturers have to either absorb the data costs of operating devices in the field, or factor in anticipated data costs to the retail price of devices.

Samsung ARTIK Cloud Monetization addresses this problem by providing a complete brokering, metering and payments system. It gives device manufacturers an easy way to make their devices interoperable with third-party devices and applications, and monetize data useage. With the Samsung ARTIK Cloud developer portal, device manufacturers have the flexibility to define service plans that meet their business needs. Samsung ARTIK Cloud brokers and meters user interactions against the defined plan, and manages upgrades, payments and revenue share back to the device OEM.

Some may quibble with Samsung's description of the service as the first of its kind, but it undeniably targets a legitimate pain point for IoT device makers.

Samsung's announcement fits into one of the four business models for IoT defined by Constellation VP and principal analyst Andy Mulholland—that of a broker. "Owners of endpoints and consumers of data in ecosystems from smart cities to transportation and alike need a middle broker who interconnects and charges," he says. "There are a host of services around categorization and context for the endpoint, as well as charging, that need to be provided. Given that Korea is one of the hottest spots for smart cities and ecosystems it would seem logical that Samsung ride their homemarket to bring this role into play. But western markets are not so advanced as to immediately be able to make use of this."

Google's native Chrome Ad-Blocker surfaces: Last month, news emerged that Google was developing a native ad-blocker for its Chrome browser. It seemed counterintuitive at first given how much Google depends on web advertising for revenue, but the idea is to block annoying ads and ultimately stop them from getting produced at all. 

Now the tool has shown up in Canary, the pre-release version of Chrome for Android, as Techcrunch notes. Google is planning to make the tool generally available sometime next year, according to previous reports.

Google has joined up with the industry group Coalition for Better Ads, a group with members including Facebook, Unilever, Proctor & Gamble, Thomson Reuters and the World Federation of Advertisers. The CBA is fighting against a dozen types of desktop and mobile ads, including auto-playing video ads with sound, large sticky ads and full-screen scrollover ads.

POV: There are already effective ad-blocking extensions for Chrome and other browsers, but marketers and advertisers should take Google's move seriously, as Chrome commands more than 60 percent of the browser market. Users who haven't installed third-party ad blockers might feel more comfortable doing so with a native tool option.

Digital transfomation keeping some tech jobs back to U.S.: The New York Times took a look at the trend toward U.S. companies looking to onshore outsourcing companies for forward-thinking IT projects. While the piece's evidence is partly anecdotal, there are plenty of interesting nuggets, such as this one:

Monty Hamilton, a former Accenture consultant, took over Rural Sourcing in 2009, when it had just a dozen employees. Today, the company has 300 workers in four delivery centers: in Albuquerque; Augusta, Ga.; Jonesboro, Ark.; and Mobile, Ala. The payroll will reach about 400 people by the end of the year, Mr. Hamilton said.

“Every business now realizes it’s a digital business,” he said. “They need technical help, and that’s really driven the demand for our U.S.-based talent.”

As the NYT notes, massive offshoring players IBM and Infosys recently announced plans to hire an additional 35,000 workers in total over the next few years.

POV: There's no indication offshoring is in any great peril, given the amount of legacy systems that still need maintenance, preferably at a low cost. But the trend outlined in the story is for real, and as such enterprises undergoing digital transformation should shape their talent procurement strategies accordingly.

Legacy watch: Petitioners hope to save Adobe Flash from extinction: Adobe's long-standing but not-exactly-loved Flash multimedia player is set to be retired, but will live on in another form if backers of a new petition on Github have their way. The solution is for Adobe to open-source Flash and the related Shockwave application builder, which would be right thing to do, the petitioners say:

Flash along with its sister project Shockwave is an important piece of Internet history and killing Flash and Shockwave means future generations can't access the past. Games, experiments and websites would be forgotten.

Open sourcing Flash and the Shockwave spec would be a good solution to keep Flash and Shockwave projects alive safely for archive reasons. Don't know how, but that's the beauty of open source: you never know what will come up after you go open source!

We understand that there can be licensed components you might not be able to release. Simply leave them out with a note explaining what was removed. We will either bypass them, or replace them with open source alternatives.

POV: It's not clear how successful the petition will be, but there's certainly ample precedent of vendors releasing discarded proprietary code as open-source. That said, Flash usage has dropped substantially over the past few years as newer options such as HTML5 took hold, so there's the question of demand going forward. Moreover, Flash was notoriously buggy and insecure—could a fledgling open-source community do better than Adobe at issuing fixes and shoring up Flash's security? It might be best to let Flash just fade away, but if you want to sign the petition, go here.

 

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Summer News Analysis - Google introduces Google Hire

Summer News Analysis - Google introduces Google Hire

What’s the news: Google wants to help recruiters be more successful. It wants them to use G-Suite to schedule appointments, Gmail to email with applicants and internal stakeholders, use Google Search to make job post more attractive. Google has also thought of reports and data migration to get started. Hire leverages assets from Bebop – the ‘acquihire’ that brought Diane Greene to Google. The link to the earlier shipped Google Jops API isn’t fully clear, but its more likely than not leveraged.

 
 
Why it matters: Recruiting or more fancy Talent Acquisition is a team sport that is highly fragmented from a systems perspective. Making it easier for the recruiter and the hiring manager is a key to make hiring decisions faster and better, which matters in a tightening jobs market and is crucial for an enterprise to accelerate. 
Google Hire Screenshots from Google's Hire website

MyPOV: Google is getting more and more in the enterprise software space / SaaS market. Good to see it knows that e.g. data migration and reports are a must for the enterprise. It will have to answer questions soon in regards of plans to offer more than recruiting capabilities, e.g. onboarding and learning come to mind. And let’s not forget the veritable market presence LinkedIn (and Microsoft) have in this space. Don’t be surprised if Microsoft ‘embraces and extends’ this automation area at some point and: Microsoft's LinkedIn acquisition makes both vendors already competitors. More competition is good for customers - making products better, licensing competitive etc. So there is little not to like of Google announcing Hire.

CxO Advice – If your recruiting team and / or company is a Google shop, definitively take a look. If not look at the value of the APIs. It’s unlikely a superior recruiting product can unseat Outlook in an enterprise – this is why all the other recruiting vendors offers interfaces to Outlook (and increasingly, G-Suite). Google may learn this in the next quarters, so stay tuned. Even if you can’t move – ask your recruiting vendors for the same features – on their platform.

 
 

 

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Silicon Valley has forgotten Com Sci 101

Silicon Valley has forgotten Com Sci 101

Artificial Intelligence is with us today.  When you fire up your smart phone’s map application, it knows where you’re probably going based on the time of day, and without prompting, gives you a bit of advice about how to get there and what traffic jam to avoid. That’s pretty cool. And from there we easily slide into an optimistic outlook for self-driving cars.

Let’s take a long hard look at the smooth-talking claims behind autonomous cars, “Big AI”, the Singularity, and the presumption that within a few years we will see a human-like awareness in computers.  Let’s start with the limits of computation.

When I did first year computer science in the 1970s, we were taught about the fundamental limits of algorithms. Logicians know with mathematical certainty that there are some things that algorithms can’t do, but Silicon Valley has forgotten the lesson, and instead is barrelling down the road of autonomous vehicles.

Algorithmic failures are deeply unpredictable. Already there have been some horrible missteps in machine vision. Recall the “racist” image classification algorithms.  The problem goes beyond developers’ bias infecting their work; it’s about an optimism that has infected the whole of the AI project.  If a computer can’t even solve the Halting Problem – predicting whether or not a program is going to stop – then what chance is there really that an autonomous car can be delegated responsibility for life-and-death decisions?

An AI engineer’s first encounter with ethics may be the Trolley Problem. But what they can fail to glean from Wikipedia is that the Trolley Problem has no resolution. The moral of the story is that our philosophical frame of reference shapes our response to life and death questions.  So it cannot be coded. We won’t ever have a program driving a car that’s going to come up with right answers all the time (or socially acceptable ones) to real life moral dilemmas. 

Think about the good old courtroom drama.  Why does this TV genre never grow old? It's because real-life problems of accountability and responsibility play out in myriad unpredictable ways.  There's always some unforseen twist - a precedent - that makes tough cases so absorbing. Even real life lawyers can't predict the outcomes of legal cases (which is why we have real life lawyers).  There is no algorithm for these things, and after a while, the AI industry is going to find that self-driving car crashes get messy. 

Nevertheless, I've heard automobile executives speculate that customers might be given a configuration option when setting up their new self-driving cars, to prioritise the life of the driver or that of the pedestrian in the event of a looming accident. If anyone thinks that a computer can be reliably programmed to make that sort of call, then that mindset is itself unethical.

We urgently need a more sophisticated way of framing AI, around an understanding that there are some things that computers just can’t do.

Every algorithm is always going to reach its limit, where it’s either going to tip into unpredictable behavior, or just grind to a halt because it can’t figure out what to do. One of the tricks in human intelligence is we seem to know when to call for help. We can realise our limitations, and pick when we need a second opinion, or seek counsel from a trusted advisor, or take a poll.  There can be no universal algorithm for detecting a responding to failure.  Any algorithm for detecting failure will itself occasionally fail, and then what will happen?

I’m not saying that there’s something mystical going on in the human brain, but there are some deep cognitive problems that we haven’t worked out yet. So I find it unethical for captains of industry to be treating self-driving cars as almost a solved problem. AI is much harder than it looks.

 

Tech Optimization Digital Safety, Privacy & Cybersecurity Chief Executive Officer Chief Information Officer Chief Digital Officer

Social Business News July 28 2017

Social Business News July 28 2017

Alan's Angle - The Social Business News Recap for the week ending July 28th, 2017

Slack raises $250M - Analytics, AI, business partners and their first customer conference

WalkMe raises $75M - Digital Adoption Platforms help guide people through enterprise applications and websites

Mitel acquires ShoreTel - How will they reconcile their overlapping UCC and collaboration tools?

Shelf.io raises $2.2M - Aggregate content from multiple repositories into a single container

Future of Work