Trends that are Changing the Way We Live
Disruption: We read about it, talk about it and experience it every day. The disruptive innovators of the world are quite literally uprooting and changing how we think, learn, communicate and behave, displacing markets, industries and technologies while they're at it.
What's ahead for us? How do we brace ourselves for yet more change? And how is NCU preparing students for disruptions in data science, artificial intelligence, cybersecurity and other areas of technology?
Dr. Robert Sapp, Dean of the School of Technology, shares his insights.
Of all the disruptions we're experiencing, which do you think are having the biggest impact?
I believe there are several areas where we're going to see big disruptions in the next 36 months. The rise in mechanization, robotics, 3D printers and the like are going to be extraordinary. We will see a much greater relationship between information technology and hard “stuff.” Cybersecurity and artificial intelligence (AI) are also evolving, so we'll continue to hear more about them.
Data science will play a more important role in many facets of our lives going forward. Nearly everything we experience online will be touched by elements of data management and analytics. NCU is now offering data science master and doctoral degrees. Importantly, all of our degrees are designed to align to the industry they support so students will gain practical, usable knowledge and skills they'll need to be ready on day one and to adapt to the rapid changes in their chosen careers.
Hasn't data science been around for a while? What is NCU doing that is new in this area?
The elements of data science have been around for a while. Things like data acquisition and manipulation, quantitative methods, predictive analytics and data visualization aren't new concepts. What is new (or at least newer) is the specific sequence of data science and its existence as a scientific discipline.
What differentiates our programs is that we teach the discipline of data science. We teach each phase of the research process in sequence, and we teach methods of transition from one phase to the next. Students learn to identify a research problem and to write and test hypotheses. They learn to acquire, audit and scrub data and how to select an appropriate statistical model. And they learn about descriptive and inferential statistics, which is a huge component in many artificial intelligence (AI) algorithms.
"I believe there are several areas where we're going to see big disruptions in the next 36 months. The rise in mechanization, robotics, 3D printers and the like are going to be extraordinary."
—Dr. Robert Sapp
They will learn to interpret the outputs from their analysis as they apply the research. Finally, they will learn how to report their findings in actionable formats, including text and data visualizations. Students who graduate from our program will be prepared for work in all areas of the discipline and, more importantly, will be able to lead an effort through all phases.
Other data science programs tend to emphasize a specific phase and not the entire discipline. Students may take courses in AI, big data and quantitative method. Their programs aren't based on the discipline, but are taught as disaggregated subjects.
At NCU, we prepare students to become data scientists. They're able see the larger context, and understand and study an entire business problem versus just one piece of it.
Our program includes a specialization in cybersecurity. How is NCU preparing students to meet the changing demands of careers in this area?
One thing we're doing with all of our programs – and we started with cybersecurity – is aligning them with specific industry organizations and standards. As soon as our first cybersecurity student graduates, we will meet the standards of the National Centers for Academic Excellence, a program jointly sponsored by the Department of Homeland Security and the National Security Agency. We have also aligned our curriculum with the Certified Information Systems Security Professional (CISSP) credential. Students who complete an MS in Cybersecurity with NCU will also be prepared to sit for the CISSP exam.
We are also very focused on making sure assignments in our courses align with the specific activities students will undertake in the industry. For example, if you read three chapters about designing a computer network based on a hard network – which means it has internal protections against cybersecurity – you won't be asked to write a paper summarizing what you read. Instead, you may be asked to identify the weakness and vulnerabilities of a network design or perhaps design one yourself. You may be given a log or a series of outputs to make determinations about the denial of service or unauthorized access.
Another thing that is relatively unique about our program is that we give assignments that continue across courses. This method of teaching helps us better assess students based on what they'll be asked to do in the workforce, where tasks are larger and may require a broader skill set beyond what can be learned in one course. Other schools tend to back off these types of assignments because they do not easily fit within a box of a single course.
You mentioned artificial intelligence (AI). Can you give an example of how AI is disrupting our society?
Artificial intelligence has been around for decades, and it's an area that is scaring the heck out of people. We hear news reports about computers beating world champions at chess or creating poetry. Right now, algorithms are very good at chewing through large datasets at unbelievable speeds. They are also capable of “learning” in that they can identify trends and patterns and predict their continuation of deviation. But generally, their creativity exists only within the parameters we provide for them. So, while we'll see more and better of the same type of programming, we don't have to worry about computers taking over the world right now.
"What differentiates our programs is that we teach the discipline of data science."
—Dr. Robert Sapp
That said, there is a tremendous benefit to AI, and it is a critical component in our computer science and data science programs. AI allows us to bring order out of huge sets of data beyond what's humanly possible. It's the force behind some remarkable advancements such as identifying behaviors that make people susceptible to a specific disease or predicting what a set of consumers might like.
AI will become even more applicable going forward. And based on what we've experienced with Facebook and Google, I believe that our knowledge of AI and big data has outpaced our wisdom. We still have so much to figure out when it comes to policy, protocols, privacy and who owns what data.
So much of disruption raises ethical questions. How do we, as citizens, better educate ourselves when it comes to ethical standards? And is this an area that our students are tackling?
Ethics as it relates to specific areas of technology appears in many of our courses. We are planning an entire course about ethics in our data science doctoral program that examines things like privacy, how we interpret and use personal data, and issues and responsibilities associated with reporting data.
An entire section of the ethics of statistics course is devoted to data visualization, a relatively new type of communication which I believe is incredibly disruptive. Data visualization has this capacity to show very complex kinds of metrics, coefficients and other difficult-to-consume data through graphics that are much easier to understand.
The problem with visualization is that there is great capacity for intentional or unintentional error and manipulation. I can show you a difference of one percent and, based on the scale, make it look like nothing – or I can make it look like it's huge. You can really show almost anything you want in data.
The American Statistical Association has released ethical guidelines for statistical practices, and there are standards about how to use these tools. Data producers need to be held to these standards. As consumers, we are also responsible to educate ourselves. We are generally able to read critically and evaluate the issues, but it's more difficult when it comes to graphics and data visualization.
Would you say that the School of Technology is somewhat of a disrupter on its own?
Absolutely. Our courses are immediately tied to the industries they support. Our assignments and assessments are based on real-world experiences. When our students graduate, they are fully prepared for any workplace scenario in their field.
We also have a huge advantage because our school is new, and our curriculum is based on current best practices, current tools and current thinking.
Please visit the NCU website for additional information about NCU's School of Technology.