nformation systems engineering emerged 20–25 years ago, when data collection, storage, retrieval and processing really became an essential aspect in the field of engineering. Despite being an undeniably useful area of study that has led to major breakthroughs, the information systems field cannot continue to be the powerhouse it once was without adapting.
Intelligent systems engineering is a field that examines the role artificial intelligence and machine learning play in the data retrieval process. This field has made significant breakthroughs and has advanced the computer science discipline in just a few years. Because of these breakthroughs, it has become increasingly important to businesses, think tanks and universities.
What is Intelligent Systems Engineering?
Intelligent systems are not coded with explicit instructions. This means critical functionality components are not accounted for in the system, which can result in safety and reliability risks, and it requires engineers to establish a thorough understanding of all parts of a system to ensure its accuracy and safety, especially as systems interact with humans.
Accuracy and safety are vital for real-world applications of intelligent systems. Autonomous vehicles, smart cities, robotics, and medical and industrial systems face unprecedented challenges because they interact with a complex ecosystem of intelligent systems whose behaviors are emergent and unpredictable. These complex systems are made more complex because they need to navigate this ecosystem while remaining fair, ethical, and socially acceptable.
How are Intelligent Systems Different from Information Systems?
Both intelligent systems engineering and information systems engineering focus on processing and retrieving data in complex systems to find insights that analysts can use to solve problems. Despite sharing a common purpose, each field has its own distinct functionality and approach.
Intelligent Systems
Intelligent systems are concerned with the design, construction, deployment and assurance of large-scale and complex systems powered by artificial intelligence and machine learning algorithms.
Artificial intelligence and machine learning systems contain components that learn, decide and behave in ways that cannot be predicted by their designers. Since they learn while they work, artificial intelligence and machine learning’s safety and reliability become more difficult to guarantee over time.
The study of intelligent systems is considered the next evolution of information systems. Systems that require the integration of complex artificial intelligence- and machine learning-powered technology are quickly emerging. Such cutting-edge technology generally falls into these key areas:
- Autonomous Systems Software
- Internet of Things
- Information Systems
- Business Systems
Information Systems
Information systems is a wider field that focuses on the development of large-scale systems that turn data into insight. This transformation requires an understanding of systems engineering and software development in order to pull data in ways that make it possible for analysts to make data-based decisions. Information systems is a well-established field, and the evolution of the discipline is unfolding in the form of intelligent systems engineering.
The classic types of information systems are often categorized as follows:
- Office Automation Systems
- Knowledge Management Systems (KM software)
- Management Information Systems (MIS)
- Transaction Processing Systems (TPS)
- Decision Support Systems (DSS)
- Executive Support System (ESS)
Intelligent Systems Engineering Jobs and Careers
The job growth projections for information systems engineering and intelligent systems engineering are both above average for the labor market. Professionals in both fields have strong analytical, managerial, and decision-making skills.
With the application of artificial intelligence and machine learning expected to increase over the years, it is likely that current engineering professionals will look to align their career advancement with the growing field of intelligent systems.
Because the discipline is in its infancy, there is a wide variety of intelligent systems engineering jobs. These career descriptions are just some examples of the types of roles you could pursue:
- Intelligent Systems Engineer
- Software/Hardware Developer
- Artificial Intelligence Specialist
- Data Science Specialist
- Machine Learning Researcher
- Machine Learning Specialist
- Machine Learning Engineer
Professionals who want to level up their careers may consider these three general pathways:
- Systems Engineer: Oversees engineering, management, and business elements of a project or system. This role is responsible for syncing all pieces and elements of a system.
- Architect: Designs hardware, software or applications, and services in data networking. This can be for any business.
- Developer: Builds and/or creates software and applications. This role involves the writing, debugging and execution of source code.
Evolving to Meet the Need: JHU EP’s Information Systems Engineering Program
At Johns Hopkins University, we recognize the evolution of artificial intelligence and machine learning and its role in shifting and advancing the field of information systems. This has presented opportunities for engineering students and businesses alike to build knowledge around this progressive discipline that can directly impact consumers. That is why we have reimagined the curriculum in our Information Systems Engineering master’s program to include elements and courses relating to intelligent systems engineering.
Graduates of this forward-thinking program will have a deep appreciation for modern artificial intelligence and machine learning technologies and design how they reliability co-exist in spaces where humans live and work. They will also be able to engineer and develop robust, trusted, and safe systems that incorporate these technologies.
Start Your Journey. Build a Better Information System backed by the power of Intelligent Systems with EP
Johns Hopkins’ Information Systems master’s program is the perfect fit for professionals who aim to engineer and build AI- and ML-powered software-based systems. Learn about prerequisites, degree requirements and coursework, or feel free to reach out to admissions with questions.