Why a Knowledge Graph May Power the Next Generation of Siri-Like Assistants

What’s the biggest complaint against Siri and other virtual personal assistants (VPAs)? The complaint I see the most is that Siri doesn’t always give you the answer, but instead displays links to a bunch of web pages and makes you do the work. Try asking Siri right now “Who built the Eiffel Tower?” Siri will display a Wikipedia blurb and map and say “Ok, here’s what I found.” It’s up to you to read through the Wikipedia text (which seems painfully small on my iPhone 6 Plus, but I’m old) and find out that Gustave Eiffel was the designer and engineer.

What is the Knowledge GraphNow try typing the same question into Google. At the top of the screen, you’ll see the names and photos of Gustave Eiffel and Stephen Sauvestre. Not only did Google answer the question directly, it actually told me something I didn’t know, which is that Eiffel wasn’t the only architect who designed the famous tower.

What technology underlies Google’s ability to answer my question directly? Anyone who follows the world of SEO knows the answer to the question is the Google Knowledge Graph. The Knowledge Graph is based on mountains of information about people, things, and their interrelationships that are housed in Wikidata (and formerly in Freebase, acquired by Google in July 2010).

Google’s Knowledge Graph has evolved into the Knowledge Vault and Jaron Collis does a great job at explaining some of the technology that powers it in this Quora response. Google leverages complex data mining and extraction algorithms to continually glean information from the web, disambiguate it, and load it into a structured graph where meaning and relationships are clearly defined and easy to query.

In my recent post on Opus Research called “The Knowledge Graph and Its Importance for Intelligent Assistance,” I look at why this technology is so important for the coming age of VPAs and enterprise intelligent assistants. If you’re a developer in the field of Big Data or Machine Learning, you may very well be building the infrastructure that powers the truly smart digital assistants of the future. Those would be the ones that can answer just about any question without making you read a web page.

What the Age of Chat Means for Intelligent Assistance

Text BubblesThere’s no disputing the fact that messaging platforms, specifically WeChat and Line, have become the most used interfaces on mobile devices in Asia. Because of the traction these platforms have gained, companies are building increasing levels of functionality on top of these services. The hottest trend is the addition of bots that users can message back and forth with as though they were human friends.

Text-based bots are emerging to perform all kinds of services, from hailing rideshare cars to ordering gifts, to figuring out the best deal on complex travel plans. There’s no doubt that these bots represent a new form of what we’ve been calling intelligent assistance.

Mobile users in North America and Europe aren’t using the messaging interface to the same extent as their counterparts in Asia. But if the trend continues, platforms such as Facebook Messenger and perhaps an upcoming Google competitor could become as dominant here as WeChat and Line are in China and Japan.

Many US-based brands are already rushing to get ready for the shift from apps to messaging platforms. What does this mean for intelligent assistants and technologies that companies have already invested in? For more depth on this topic, check out my latest post on Opus Research called “Why Text-Based Commerce is the Future of Intelligent Assistance.”

 

Joining the Opus Research Team!

Opus ResearchFor the past three years, I’ve been writing the Virtual Agent Chat blog in my spare time. My main goal was to learn as much as I could about the evolving world of intelligent assistants, both enterprise and personal assistants. I’ve been exploring the technologies, vendors, and market trends and providing my own perspective along the way.

The outstanding team at Opus Research was kind enough to invite me to participate in their pathfinding Intelligent Assistants Conferences and even to include me as a judge in their Intelligent Assistant Awards over the past two years. I’ve enjoyed learning from the insights of Dan Miller and Derek Top and publishing the occasional guest blog post on the Opus site.

With my recent retirement from federal service, the Opus Research team has invited me to join their team as an analyst. I’m glad to take them up on this opportunity and I really look forward to continuing to learn and write about the intelligent assistant space as an analyst for Opus.

While most of my blogging will happen on the Opus Research site, I’ll continue to post updates and links here. There’s lots to discover and discuss in this quickly evolving space. I hope you’ll join the conversation on the Opus site and on our various social media platforms. See you there!

2015 Retrospective of Intelligent Assistants and Look Ahead to 2016

20162015 saw lots of buzz about artificial intelligence, deep learning, and automation. There were also many exciting developments in the world of customer-facing enterprise intelligent assistants and consumer-focused virtual personal assistants. I wrote about as many of these developments as I could throughout the year in this blog.

I recently published a guest post on the Opus Research site in which I share my key takeaways for the intelligent assistant space in 2015. Dan Miller of Opus Research published a companion article with his look ahead to 2016 and his very interesting take on how companies should be wary about making false choices when they implement self-service technologies in the New Year.

Companies that implemented or built upon existing enterprise intelligent assistance solutions in 2015 reaped big benefits.  In 2016, it’s time to keep pressing ahead or, for those who haven’t started yet, get caught up before it’s too late.

Go Moment Ivy is a Chat-Based Virtual Concierge

I recently saw a webinar by Tom Austin of Gartner on the topic of Smart Machine Big Bang Disruption. During the presentation, Austin mentioned the company Go Moment as an example of an intelligent assistant that provides many benefits, while at the same time disrupting longstanding patterns of customer service.

Go Moment IvyHotels use Go Moment’s Ivy to provide guests with a virtual assistant concierge. Guests interact with Ivy using text messages. I recently noted how much buzz there is around chat-based customer service interactions. An SMS-based smart hotel concierge is yet another indication of the growing significance of chat in the customer service realm.

In his webinar, Austin notes that the rise of smart machines offers both opportunities and risks. Companies stand to save money by automating tasks traditionally performed by humans. At the same time, they need to help workers acquire skills that enable them to leverage smart machines to excel.

Go Moment’s Ivy can answer many of a hotel guest’s common questions, lessening their need to call the front desk or guest services. An article in Hotel Online takes the stance that Go Moment’s technology frees up human hotel personnel to assist guests with more complex questions and transactions that require the human touch.

According to the same Hotel Online article, Go Moment leverages IBM’s Watson platform to power the app’s natural language processing and question and answering system.

Ivy seems to be a logical progression from Go Moment’s earlier product called CAPE. CAPE was an SMS-based platform the enabled human hotel staffers to interact with guests using text messages. Ivy now automates many of those interactions, answering the low-hanging fruit of FAQs. In the Ivy demo, Ivy responds to questions such as “when is breakfast served” and “what’s the Wifi password?”

Ivy can also query guests about how they’d rate their stay. If they view their stay positively, Ivy can prompt them to write an online review. If the guest isn’t completely happy, Ivy alerts a human staffer who can seek to make things right before the guest posts a potentially damaging review.

Intelligent machines are likely to automate an increasing percentage of the transactions that were once human-to-human. The first challenge is to make those interactions truly beneficial to the customer on the other side of the conversation. The second is to ensure the human who used to be across from the customer can now add even more value to the service equation.

Gartner’s Strategic Predictions Spotlight Digital Assistants

Gartner Strategic Predictions 2016Gartner recently published their Top Strategic Predictions for 2016 and Beyond. Gartner is projecting a substantial role for smart machines and digital assistants in the enterprise over the next few years. Looking towards 2020, Gartner is even more bullish on the market for smart digital devices. At the same time, the research and advisory firm warns of the coming disruption that enterprises and workers are likely to encounter as smart machines become ever more prevalent.  

Out of their top predictions, let’s take a closer look at the following two:

By YE18, customer digital assistants will recognize individuals by face and voice across channels and partners.

Gartner is betting that customer digital assistants will increasingly be outfitted to recognize individual customers. Gartner believes that these assistants will leverage front-facing smartphone cameras to identify customers and use smartphone microphones for voice recognition.

Gartner’s overall predictions for how customer digital assistants will evolve over the next several years are quite ambitious. Their report describes a scenario in which a customer uses her phone so that a retail brand’s digital assistant can recognize her and check her in when she arrives at the store. The assistant picks up the conversation with the customer where it left off when they last interacted.

Another assistant embedded in the dressing room mirror converses with the customer to recommend additional clothing pieces that match her ensemble based on what it knows is in stock and on sale in her size. The assistant even executes the payment transaction so that the customer never has to stand in a check-out line.

Gartner recommends that companies and brands serving customers quickly start adopting customer digital assistant technologies. They note that a tremendous advantage of these technologies is their  “pull” or “opt-in” engagement pattern. Customers can choose to interact with the assistant when and where they need to for optimal service, instead of being interrupted by unsolicited messages they don’t want.

By 2020, smart agents will facilitate 40% of mobile interactions, and the post­app era will begin to dominate.

Gartner predicts that our fascination with apps is about to give way to app fatigue and a desire for a simpler, more seamless way to engage with digital services. Gartner sees the coming wave of virtual personal assistants (VPAs) as the new user interface of choice. For one thing, VPAs are easier to interact with via voice or text-driven conversational interfaces.

But the biggest advantage of VPAs is that they will leverage machine learning and rich data models to understand us and predict what we want and need. They will also learn how to execute many of the repetitive and even complex tasks that we perform daily and take care of those tasks for us. No longer burdened with mundane workflows, we’ll have time to carry out more creative pursuits.

Gartner notes that there is still much to explore around the implications for our privacy. But the potential gains in workforce productivity make it imperative that businesses continue to press forward. Gartner encourages businesses to aggressively plan for what they term the “post-app” era. Developing a strategy for VPAs should be at the forefront of that planning.

The Risk of Virtual Personal Assistants as Gatekeepers

Virtual personal assistants( VPAs) are software applications that understand written and spoken text, that speak, answer questions, provide useful information, and perform tasks for us. VPAs rely on capabilities ranging from speech recognition to predictive analytics and machine learning algorithms. Siri and Google Now are the most widely used VPAs. As the technologies advance, our VPAs are expected to become increasingly capable.

Neural NetworksIn a recent article, Tom Pullar-Strecker speculates that VPAs will have deep knowledge of us and our preferences. We will depend on these smart assistants to help us plan and organize our lives and even carry out basic tasks. Our VPA will determine if we’re available to meet with friends and then arrange the entire evening for us, from inviting our guests to making the restaurant reservations. The VPA will also act as gatekeeper to block unwanted corporate advertisements from reaching us. It will filter ads and only show us products that it believes we’ll be interested in, based on its knowledge of us.

We’re entering a new world. A VPA that has all these abilities can be a huge asset to us and to those around us. But are there dangers lurking behind this seemingly positive future scenario? Most concerns that are voiced seem to be around privacy. For the VPA to be truly effective, it will require deep insights into my personality, habits, and health. It will need to know who my family members are, as well as my friends and co-workers. Many are worried about the implications of providing so much data to a VPA.

But there are other risks that aren’t discussed as often as the topic of privacy. A risk that hasn’t been addressed much is the risk of what I’ll call unfair VPA filtering. If my VPA protects me from unwanted ads or solicitations, and if it has my permission to make purchases on my behalf, it will wield a lot of power. Companies are going to want the VPA to approve their products, instead of filtering them out. How will the VPA decide which pair of shoes it should buy for me, when it feels that I’d be happy with any of 5 different selections? The VPA, or whoever controls the VPA, could just buy the shoes from the company that pays the most to have me as their customer. It gets a kickback from every transaction it executes on my behalf.

I explore this risk in a recent guest post on Opus Research entitled: Virtual Personal Assistants: Future Gatekeeper to Your Attention? You can also join the conversation on Opus Research’s LinkedIn Group for Intelligent Assistants Developers and Implementers.