Cognitive Computing and Frontiers
I recently had the honor of participating in the Tech Fellows kickoff with Engility Corporation, where I serve as a Systems Engineer and a Tech Fellow. I am very excited about this opportunity to research cognitive computing to enhance advanced analytics in our corporation and for our customers. Cognitive computing is the simulation of human thought processes in a computerized model to include self-learning systems that use analytics, algorithms, pattern recognition and natural language processing. Cognitive computing could be an enabler, subset, or element of a larger set of capabilities known as artificial intelligence. I prefer IBM's use of the term "augmented intelligence" to describe the growing and enabling capabilities that are changing life across the planet.
The goal of my project is to capture a variety of use cases for AI (artificial or augmented intelligence) to accelerate decision making, analysis, and insight for internal corporate considerations and for enhancing solutions, services, and products for our customers and partners.
The inspiration for my project comes from interest and curiosity about decision making. The data and computing power available astounds me and inspires me to discover, identify, and use the various tools and technologies to make better fact-based, data-informed decisions. The various prognostications for AI in 2017 keep growing, and information coming from think tanks, government, consultants, and research increases my interests. For example, the Office of Science and Technology Policy describes the environment in their recent paper:
Accelerating artificial intelligence (AI) capabilities will enable automation of some tasks that have long required human labor. These transformations will open up new opportunities for individuals, the economy, and society, but they have the potential to disrupt the current livelihoods of millions of Americans. Whether AI leads to unemployment and increases in inequality over the long-run depends not only on the technology itself but also on the institutions and policies that are in place. This report examines the expected impact of AI-driven automation on the economy, and describes broad strategies that could increase the benefits of AI and mitigate its costs.
One of the salient sentences in the paper stated, "There are many opportunities for AI and specifically machine-learning systems to help cope with the sheer complexity of cyberspace and support effective human decision making." I agree wholeheartedly and extend the many opportunities to systems engineering, intelligence analysis, business development, technology, and a host of business processes.
Another of my inspirations came from the November 2016 edition of WIRED magazine. In this special issue, the guest editor was President Barak Obama. The issue focused on the idea of frontiers. The frontiers included looking ahead to push the limits in four areas described as personal, local, national, and international. The frontiers are a challenge to think beyond the noise and limitation of today and find solutions for confronting problems or perceived obstacles in the four levels.
I find utility and inspiration in each frontier level. Aspects of concern related to AI are apparent in the many science fiction novels and movies that depict computers taking over or how AI can displace or replace some workers or be used in malevolent ways. Mark Zuckerberg, founder, and CEO of Facebook, succinctly addresses these issues related to ensuring that artificial intelligence helps rather than hurts us. Mark suggests that we should not be afraid of technologies and the science fiction that seem to cast AI in doomsday scenarios. We should carefully develop AI and be cognizant of all the beneficial applications, especially the benefits for improving our lives. He highlights the example of how AI is saving lives in the health industry as only the beginning of how AI can improve the future.
The promise and potential of AI are to unlock value in massive amounts of data to augment human action. When we understand the multiple data sets that can inform our thought processes and decision making, we can make better decisions which lead to more optimal results. One of my favorite knowledge models is DIKAR (data, information, knowledge, action, results). In a hyperdata world, we cannot process the D-I-K elements fast enough to move to the A element to get the result (R element) that we desire. In my project, my deliverable will outline and prescribe use cases for achieving the full DIKAR cycle faster with more informed and prepared actions. The intended result of the project is better outcomes and results based on augmented intelligence and leveraging of the computing power.
As I go through this journey, I will share, collaborate, and engage those who share an interest in AI and improving decision making, actions, and results. The initial learning cycle will also be useful for applying to a variety of challenges, opportunities, and frontiers. I appreciate thoughts and ideas to inform and guide the journey as we push the technical, cultural, and business frontiers.
