People are amazing. They go about their day interacting with thousands of complex inanimate objects, generating and consuming vast amounts of information with ease, making sense of it all for themselves and others, and sometimes even creating value along the way.
Unable to interpret messy human information, machines have needed people to do it for them. And for that reason, machines have so far just been part of that inanimate world I mentioned, more a thing to touch and a challenge for the human brain to overcome than an equal partner and a helper.
But this is changing - rapidly. After recent advances in machine learning and artificial intelligence, humans are no longer unique in their ability to make sense of the world - and make sense of other humans. This sweeping change, inspiring and frightening in its implications, is why the business world is scrambling to exploit the competitive advantages available through proper application of machine learning, artificial intelligence (AI), the internet of things (IoT), and blockchain (while remembering to manage cybersecurity challenges).
Much of the work that has been done on AI and machine learning is centered on recognizing real signals and real data in the overall pattern of human activity, and then extracting that data out from the noise to allow people to deal with the strategic endpoints. Meanwhile, the Internet of Things (IoT) is making hitherto unthinkable volumes of detailed data about everyday life available for machine analysis.
These cutting edge technologies are imperfect and will be evolving for some time, businesses will be playing a game of hopscotch, continually fighting to better their competitors. Tech companies and custom software developers like DOOR3 are laser-focused on creating ways to mitigate human messiness in the workplace, in the home, on the road and anywhere else humans live, work or explore, and through these improvements, to enable new competitive advantages for their clients.
Let’s take a look at each of these technologies in detail.
Traditional computing required people to simplify messy human information into prescribed formats and enter the information into a system; other people would then use or interact with this information. In many ways, traditional computer systems are like strict prison wardens, prescribing exactly how people should communicate to each other (through the system) and eliminating the freedom on natural human interactions - and often causing confusion and delays along the way.
Is there a better way? It turns out that recent advances now enable machines to take in stride the messiness of human behavior rather than forcing people to be unnaturally (and unreliably) regimented. With machine learning, both back-end processing and front-end interaction paradigms are becoming more and more adaptable to human communication styles. Front-end technologies like chatbots are interfacing machines and people in more human, intuitive ways, while back-end machine learning software gets enough meaning out of all that human chatter to perform meaningful work with the resulting data.
What does all that translate into? Reduced technology-induced friction between a person’s intent and completion of a task, reduced labor costs in sales, transaction support, and customer service (for starters), and greater customer satisfaction.
Even if I don’t finish my sentence, a chatbot can interpret what I was trying to say and complete the thought for me. If I stream a favorite blues artist, machine learning will curate similar music tracks and artists into a personalized playlist. Or, if I say something in a colloquial way, natural language processing will enable a chatbot to still deduce my purpose based on the context of the last three or four things I said earlier.
Manual, mistake-prone procedures will soon be a thing of the past. For every insurance broker who sends an underwriter a photo of his napkin where he scribbled some claims data for a client, there will be a better, smarter system to make sense of that messy submission and facilitate the claims and underwriting process.
When this heuristic intelligence wasn’t as advanced as it is today, people would just skip the technology altogether and handle it over the phone. But the inflection point we’ve reached in machine learning capability means that eliminating all those inefficient workarounds by facilitating this fragile human-machine interface is where it’s at right now.
Do you know what your competitors are doing to streamline business with chatbots, information ingestion engines and other machine learning-enabled techniques?
Machine learning is able to find commercially valuable patterns and trends in operational data, customer information, and transaction histories. This information by-product of normal operations is sometimes more valuable to the market than the goods and services the business produces.
Suddenly, non-revenue-generating games that learn about players’ predilections through their playing style could produce data worth millions to advertisers. Consumer buying patterns at mall food courts can suddenly predict spending in clothing stores, and so on.
Human endpoints are becoming more varied; we are no longer confined to just a keyboard and a mouse. Now you can have conversations with a smart digital assistant that can hear you clear across the room.
When you ask a digital assistant “how much does flour cost?” it knows you’re not asking “how much does a flower cost?” Or, it can ask you whether you meant rose or tulip or did you mean baking flour. These kinds of variations in smart machines now occupying our living and working spaces, our audio and visual spaces, and our digital spaces are changing the way we live our lives and freeing us up to spend more time on more valuable tasks.
Enabling highly intelligent, just in time, contextually sensitive interactions with machine intelligence via modalities that are comfortable for people, like video or audio, is among the more remarkable trends to watch. While it’s not 100% mature yet, the signs point to potentially revolutionary applications of the technology at home and at work.
Whereas machine learning is largely about recognizing patterns in complex, sometimes messy data, AI goes further by letting machines make intelligent, reasonably accurate choices.
As an example of this difference, facial recognition and speech-to-text can often be facilitated by machine learning approaches; on the other hand, a self-driving car is truly an AI since it not only recognizes patterns in the outside world but takes intelligent action to keep the car safe and traveling to its destination.
We already know self-driving trucks and buses are coming. Now imagine AI workflow supervisors (in any industry), insurance claims adjusters, and mortgage underwriters. Are you ready?
Fundamentally, IoT is about people and activities, not “things.” Indeed, the internet of things is pointless in and of itself. It only becomes meaningful when enormous data flows are parsed through machine learning, AI and big data to render actionable intelligence.
The IoT monitors human activity and constantly measures how the things around people are meeting their needs. This intelligence is allowing companies to better understand the needs and activities of people and to make the appropriate adjustments on the fly, anywhere and at any time.
Take something as mundane as the office coffee machine. Imagine being able to correlate the amount of coffee that’s consumed day by day with productivity and billable hours? What would data like that mean? Would it mean if you provide more coffee you can get more billable hours from your team, or would it mean people are spending all of their time in the office kitchen? How can you use data like this to make your team more productive and your business more profitable?
Trendwatching is hard when you have no information. The IoT can give you valuable information across a variety of dimensions that you can correlate to extract valuable insight.
Are you clear on what place IoT does or does not have in your business model and competitive landscape?
Blockchain is newer than the other trends. Until 2017, blockchain had been primarily of interest to cryptocurrency specialists. But blockchain is proving to be an effective channel for everything from contract management and bill payments to information storage and accountability between transacting parties in any number of business domains.
Moreover, blockchain is disrupting the model where brokers and intermediaries run the world in favor of a model where providers of secure transaction channels make the money that brokers used to make.
At its core, blockchain is a distributed registry that can be used to create fault-tolerant, impossible-to-destroy copies all over the world. It creates a network that can carry payloads and create accountability between contracting parties securely without intermediaries, whether used in a proprietary or nonproprietary way. It’s very powerful in cases where ownership of information are exchanged because it can be done more efficiently, better, safer, more controlled or less controlled, than can be done in more “traditional” ways.
The power, privacy, and lack of central control are liberating but also threatening to some businesses and to sovereign nations, prompting worry and and legislative attempts at regulation of a technology that is still poorly understood among the legislators themselves. These efforts are primarily aimed at cryptocurrency applications of blockchain, but any discussion of blockchain applications should include legal and political considerations.
Business process management (BPM) tools have been used for decades to streamline business processes and automate routine tasks. While the BPM path has been fruitful for many companies, it is complex and time-consuming to implement. RPA simplifies the on-ramp for enterprises seeking a nimble, quick way to automation. RPA can prove the business value of automation and clear the way for a full-on BPM initiative.
A key trend to watch is the intersection of RPA and artificial intelligence. In its simplest form RPA is simply the copying of end-user UI actions by “robotic imitator” software, making the most basic decisions based on task data. For example, opening an email attachment, and based on hard rules about the content, forwarding that email to the appropriate human handler. However, once AI is added to the mix, RPA may become capable of learning very complex end-user activities, and going beyond rote data management tasks toward expert “knowledge work” that was once thought to be the exclusive domain of skilled human workers (rating the risk of credit applicants at a bank, for example).
It is too early to tell how far current AI technologies can go, but the velocity of change here is fast and growing faster, so a quarterly review is warranted.
While blockchain is secure, relatively speaking, people in organizations are not quite as disciplined. A common misconception held by many is that hacking is a pure technology play. But it’s not. Rather, it’s people who are “hacked” by falling into the traps the hacker has set. Finding ways to combat this slightly digital, mostly human attack type remains one of the unsolved problems in the digital space.
Dealing with the complex issues of securing information in the face of human fallibility is going to be the challenge of 2018 and beyond.
Which new machine learning-enabled email filters, AI, or RPA approaches will look for spoof activity and provide supplemental vigilance? Time will tell.
Considering the constant stream of new technologies and custom software that resides in the upper stratosphere of technology advancement, there are a lot of companies getting left behind because they don’t have the basic technology infrastructure to do digital effectively.
If you’re still working with a hodgepodge of different technologies gathered from multiple vendors, aging legacy systems or just making do, your mountain to climb is very high. You need to lay a foundation, and that’s something DOOR3 can help you with. We can help you improve how your business operates through custom software design and digital consulting that is aligned with your near- and long-term goals, and takes into account the full breadth of opportunity afforded by the latest technology trends. To learn more, contact us.
As the great author and physician Khaled Hosseini said, “If culture was a house, language would be the key to the front door and all of the rooms.” There is...
As a client, I often get estimates and start thinking that now I know what exactly I’m going to receive and when it will be ready. I’m waiting for my...