The Future is Now: Harnessing AI, Data Science, and Machine Learning

Empowering employees with professional education from Johns Hopkins Whiting School of Engineering Lifelong Learning will enable corporations to leverage technological advances to meet future challenges and drive success.

Technology continues to advance at a breathtaking pace. These advancements have become more pronounced with the advent and increased use of artificial intelligence (AI), data science, and machine learning (ML). Now, there is a new AI and ML-induced revolution every week. This also coincides with the growing importance of the management and analysis of vast swathes of data that have become the lifeblood of many corporations.

Bloomberg Intelligence predicts that the generative AI market will be worth $1.3 trillion by 2032. Corporations worldwide will compete—or already are competing—for their share of this market.

Corporations and global enterprises ignore these modern technologies at their peril. Much like those who struggled to adapt to the Internet of Things (IoT), the risk of getting passed on the superhighways technological progress is too great.

Hidden under these shiny advancements, however, are the ethical dilemmas and risks of AI adoption and data mismanagement. Ignoring these risks can result in numerous negative downstream impacts and places added importance on knowing how to best utilize these revolutionary technologies.

As such, it is more important than ever before for corporations to harness these advances and provide professional and executive education about AI, data science, and machine learning to employees. These educational opportunities will not only ensure that corporations can use these technologies to positively impact their bottom line, but also use them in an ethical way that benefits society.

What is the difference between AI, data science, and machine learning?

AI, data science, and machine learning have become part of our lexicon, but these terms have often been treated as interchangeable, which is not the case. While many of these fields are related, they do have their specific tasks. It is important to understand these terms to best determine how to empower your employees with these advanced and revolutionary technologies.

For instance, computers—and how humans interact with machines—have evolved. This is due to advances in data science and analytics, or how we process data and analyze data to gain insight and understanding. These advances in data have led to an explosion in AI. These advances have now made it possible for increasingly intelligent machines to perform autonomous tasks and mirror human abilities, including speech, image recognition, and problem-solving. Machine learning, on the other hand, is usually considered a subset of AI that occurs when machines learn from data and analysis without being specifically programmed to do so.

All three fields have a vast potential to positively impact our society and have become vital instruments for corporations to harness. Businesses that empower their employees with education in these fields will set themselves up for success.

 Johns Hopkins University, for instance, has found that these three fields have a variety of applications over a wide range of areas, including national security, societal safety, materials design, public health, neuroscience, space systems, and more. These fields have grown so much that the university is creating its own Data Science and AI Institute within the Whiting School of Engineering.

Importance of responsible AI and data usage

AI, data science, and ML have the potential to positively impact our global communities in multiple ways. For example, Johns Hopkins researchers recently used AI, teamed with medical professionals, to map the abdomen and create AbdomenAtlas-8K, a multi-organ dataset that can aid in medical diagnosis. This demonstrates how experts can leverage AI applications and tools to better the communities they serve.

However, not all AI and data are used responsibly. Even a casual look at recent headlines will show negative AI use cases, including fraudulent art, aiding plagiarism, or creating fake images that could be used as part of a disinformation campaign. A Johns Hopkins computer scientist even found that AI image generators could be tricked into making NSFW content.

AI aside, consumers have grown accustomed to sharing their data but have also become more aware of how data is used (or misused). Consumers want to do business with corporations that safeguard their vast amounts of data, especially those used in cloud computing. This raises the stakes for corporations as big data—and its ethical use and management—has become the lifeblood of any business and its reputation.

Harnessing AI and data science will drive success for corporations

Corporations must harness AI, data science, and machine learning to leverage these tools and drive future success. For instance, even as ChatGPT and other AI solutions have seeped into many facets of our lives, there remains a need to understand how these tools work and their limitations, including the wide variety of problems they may present, and the way humans interact with them.

AI, data science, and ML will continue to become more important to corporations. The Wall Street Journal reported that CFOs are beginning to incorporate AI and other automation tools to improve efficiencies within operations and are even using ML to help make predictions. Imagine the possibilities of incorporating these technologies into your supply chains, for instance.

If your corporation is looking to leverage these advances, it is more important than ever before that employees receive the most current professional education in these fields. It is equally important that this education also encourages the ethical use and management of AI, data science, and ML for the betterment of our shared communities.

Why does empowering employees with the latest professional education build resilient corporations?

Corporations that invest in professional and executive education for their employees can often point to a financial return on investment, but it’s not all dollars and cents.

Executive education or professional education programs provide business leaders with an educational background and skills that enable them—and the teams they lead—to solve complex challenges. It also provides a valuable opportunity for leaders to broaden their horizons by working with—and learning from—subject matter experts and their industry peers.

Additionally, a corporation that invests in the development of its people is better positioned to succeed. In constantly evolving and expanding fields like AI or data science, this could be the difference between bringing the next breakthrough to market or watching a competitor take a share of the market.

By providing a strong AI, data science, or machine learning foundation—centered on positive human values and ethics— corporations are setting their employees up for future success and tapping into the AI and data revolution.

Join the AI Revolution with Johns Hopkins Whiting School of Engineering Lifelong Learning

Partnering with the Johns Hopkins Whiting School of Engineering Lifelong Learning for executive and professional education ensures employees are empowered to stay at the forefront of constantly evolving fields in AI, data science, machine learning, cybersecurity, computer science, and more. Current courses include:

• Assurance of AI-Enabled Systems
• AI in Healthcare
• AI for Executives
• Leading Data and AI-Enabled Organizations: For Senior Leaders (United States government)

These intensive programs go beyond typical professional development or executive education and provide real-world use cases and hard-won lessons taught by world-renowned faculty and subject matter experts—including those trusted by the federal government—with flexible learning schedules and modalities for working professionals.

Reach out today to learn more about the Johns Hopkins Whiting School of Engineering Lifelong Learning, including course offerings, types of educational modalities, and more.