In the Crow Canyon blog, we’ve had several articles about Artificial Intelligence (AI) and machine learning, covering Microsoft’s embracing of the technology and the implications of that. We’ve discussed predictive analytics, the problem with Delve, and Office 365’s new personalized search capability.
This September’s Ignite conference went into detail about Microsoft’s AI-related progress – unsurprisingly, Microsoft is expanding its use of AI in a variety of its products. Let’s look at what is driving this initiative and the issues surrounding it.
Microsoft Expands Use of Artificial Intelligence
In the first three years of life, the brain of a human child is a chaotic hive of rapid activity: neurons are formed, millions of new connections are made, and synapses are born, creating a dense network of electrical and chemical connections. In the first three years, a child’s brain has up to twice as many synapses as it will have in adulthood.
This unbelievably rapid growth is not dissimilar from the gains being made right now in the field of Artificial Intelligence. With one of the largest bank accounts in the IT space, Microsoft is well-poised to drive this progress.
Obviously, Microsoft is not a research facility — the company sells software. But the laptops, tablets, and smartphones that use its software have become the lab environments of 2017; instead of white-coated scientists, we have an entire population of IT users (that is, just about everyone) contributing to this AI experiment. Every 16-year old teen using Yammer and every 45-year old professional using SharePoint are adding to a body of AI knowledge that’s feeding data to Microsoft products like Graph, MyAnalytics, and Office 365.
So how does all this translate into the day-to-day lives of Microsoft users? Let’s explore.
Enterprise Search – Search on Steroids
Not that long ago the big news was about Personalized Search. In short, Office 365 search results would now include people whose skills, interests, and projects are relevant to your search query.
A mere two months after this announcement, the real news appeared: Enterprise Search. To put it simply, the idea is that when in the Microsoft world, you can search from just about anywhere and retrieve just about anything. The goal is to enable users to search from wherever they are, such as SharePoint, MyAnalytics (formerly Delve), Office 365, and so on, using whatever device, and retrieve results from any local environment, such as sites, files, people, e-mail, documents, etc.
In addition, a new variant of Bing—“Bing for Business”—will allow users to retrieve corporate data from Microsoft’s own Internet-based search engine.
This concept of accessing data across all applications is fueled by a singular technology: Microsoft Graph.
Microsoft Graph — formerly known as Office Graph
“Office Graph” has become “Microsoft Graph”, as the scope of Microsoft’s AI initiatives have rapidly expanded to include nearly every facet of existing applications and all new development at Microsoft. The Graph API universe—like the synapses of a toddler’s brain—is branching out in every feasible direction, looking for new ways to connect and convey data.
Graph APIs are now available (or in-the-works) for Azure AD, Outlook, O365 Groups, OneDrive, Excel, Planner, OneNote, SharePoint sites, Teams, Insights, SharePoint Lists, Outlook tasks, Intune, O365 Reporting, and Dynamics.
Two Approaches – Optimist or Skeptic?
So what does this mean for the future of Office 365 and, indeed, the future of office work in general? The answer, in part, depends on where your personality lies on the Optimistic Technologist vs. Wary Skeptic scale.
The Optimistic Technologist Approach
Breaking free of its Office 365 bonds, Microsoft Graph has now become the central hub of the Microsoft universe. The technology demolishes application barriers by making cross-product content available to you regardless of the application you’re working on at the moment.
Are you sending a meeting invite in Outlook, but want to discover which colleagues have used a shared file? Or want to know which colleagues are the most likely to be interested in the meeting topic? Perhaps you’re setting up a new Communication Site and need to find co-workers who have specific knowledge about JavaScript development.
These are just some of the scenarios in which Microsoft Graph can assist. The technology connects multiple data sets and uses machine learning to offer results that are meaningful and relevant to you. In addition, based on how you interact and use Microsoft platforms, Graph can helpfully suggest content in multiple situations, such as when you perform a search or when you’re creating a new SharePoint team site. Graph’s predictive analytics capabilities anticipate your unique interests without the need for you to manually discover and enter content.
Artificial Intelligence is a powerful technology that saves you time and effort. AI helps to automate your content needs, enabling you to spend time being productive instead of wasting it searching for information.
The Wary Skeptic Approach
Artificial Intelligence is indeed a powerful technology that is here to stay, but its rapid growth and popularity tends to overshadow other facets that can pose a significant threat to businesses. While accessibility to content is a positive, unfettered transparency can present security risks to both users and regulatory-sensitive organizations.
Although a philosophical and moral argument can certainly be made about user privacy and the relinquishment of content ownership rights, a more practical issue centers on the unauthorized sharing of internal corporate data. By default, technologies such as Microsoft Graph assume that all user-created content is up-for-grabs and available for sharing and content population.
Security measures are not keeping pace with the AI interconnections being made in a typical Microsoft enterprise environment. A wide variance of APIs—many developed by Microsoft but many developed externally—are enabling applications to freely share user content. Like holding sand in a closed fist, it is nearly impossible to stop data leakage given the rapid growth of connected systems and app-specific security configurations. Even the most robust and holistic security systems cannot protect every single file — the growth of artificial intelligence, predictive analytics, and machine learning is simply overpowering efforts to secure data.
Simply locking away all secure data in an off-network location may solve the problem, but it’s not a realistic solution for companies that need to share content internally, but also need to control which content can be shared.
Concerns about Artificial Intelligence
At the moment, administrative controls enable Security Administrators to turn certain AI features on and off. For regulatory-aware organizations, this solution may be a viable approach in the near term. In five or ten years from now, when AI technology is even more widely accepted, this level of control may no longer be an option.
While security is a significant concern with Microsoft Graph, AI also raises a number of other fundamental questions. Should employees always be offered predictive content? Does this compromise creativity and independent thinking? See our article, The Problem with Delve, for more on this.
Currently, AI-powered search engines present results that are driven by objective standards such as relevant local results. In the future, will this standard also become configurable and subjective, subject to manipulation? Administrators will likely be able to configure AI to give priority to particular types of content in search results, such as that preferred by the corporation or content sponsored by corporate investors.
We will explore these and other concerns about AI more in future blogs.
Conclusion
Artificial Intelligence presents many opportunities, but also poses significant risks. The IT world is marching inexorably in this direction, but the end results may not be as sanguine as the promulgators profess it to be. Certainly, a degree of skepticism and caution is required; will we see a considered, measured approach, or will the rapid growth of AI overwhelm any objections?
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