It is time for some of us building software to take a hard look in the mirror.
For years, we promised technology would solve the world’s information management problems, but 85% of business information is still “dark data,” potentially useful insights lost in a rising tide of disconnected documents, emails, Slack conversations, voice-to-text messages, and myriad other forms.
As the digital transformation accelerates, the sheer volume and opacity of documents make it harder to ensure quality, consistency, accountability, and regulatory compliance.
What does document dysfunction look like?
Now multiply those cases by hundreds of thousands of companies and organizations around the world. That’s document dysfunction.
Right now, there are lots of smart people working to use artificial intelligence to tackle mind-boggling problems like asteroid mining or AI enhanced humans.
We think that is great, but we are focused on using AI to solve much more mundane problems. We are a document engineering company, and we think AI can solve the information management problems that afflict businesses large and small.
If that sounds boring compared to human settlements on Mars, that is okay.
We think “Boring AI” could be a pretty big deal.
We know we are not the only people thinking about these issues — researchers and academics and other luminaries have been raising these issues for years. But we think science and technology have advanced to the point where we can finally solve these problems.
We see five principles that can lead us to more effective solutions:
Of course, we need to apply artificial intelligence in natural language processing using machine learning methods like neural networks or Bayesian techniques. But we also need other disciplines like image processing and recognition, semi-structured information, declarative markup, and even approaches inspired by natural sciences like the theories of cognition and evolution. Breaking down the walls and combining these disciplines will give us new ways to solve these very hard problems.
There is a lot of this “Small Data,” and each company’s small data is different. What people call Big Data artificial intelligence these days is usually just highly supervised machine learning on massive datasets. The preparation of those datasets is labor intensive and prohibitively expensive for most individual companies. We need algorithms that are smart enough to figure out your specific documents in your company or even your division within your company, in a potentially small volume, with only minimal learning and guidance.
As an industry, it’s fine to develop and hone algorithms using massive amounts of publicly available documents and data sets, but we should not use learning from one customer to train algorithms for use with other customers. At a time when some are looking to combine data from multiple customers to increase their insights, raising questions about privacy and security, we believe it is better to treat each customer’s data as its own unique universe.
Algorithms need to understand the structure and strategy behind a company’s business documents, not just the co-occurrence of individual words and phrases. If we can create tools that can understand the different portions of a document, and their unique usages in an individual company, COOs will have powerful new ways to accelerate performance, monitor accountability, and ensure legal and regulatory compliance.
From the start, AI should enrich the tools and routines that frontline workers already use to get their work done. The past 50 years have proven that you cannot force employees to adapt to straitjacket templates, you have to provide solutions that fit into how they already work, and reduce their repetitive tasks to foster their creativity. The more users accept the AI’s help, the smarter and more helpful the AI will become. It’s a virtuous cycle.
It is fashionable to say that “AI is going to take our jobs,” but we can do better. Companies that focus on AI to cut costs may do okay in the short run, but companies that use AI to empower their frontline workers and drive their strategic advantage will be the real winners.
We don’t think that’s boring at all.
And we look forward to working with others across the industry to make that future a reality.
Tell us your document dysfunction horror stories, or your dream for how technology could give you greater efficiency and control. Or maybe you completely disagree and have never met a dysfunctional document in your life. Or maybe you think our principles are all wrong — we’d still like to hear from you!
Join the document dysfunction conversation on Twitter.
Contact us at Docugami.com.