NJIT's David Bader on the Future of AI: Silver Linings, a Touch of Grey

Written by: Evan Koblentz

Artificial intelligence, data science and the emerging field of quantum computing are among the hottest research topics in computing overall. David Bader, a distinguished professor in NJIT’s Ying Wu College of Computing and director of the university’s Institute for Data Science, shared his thoughts on big-picture questions about each area. Bader is known globally for his innovative work in the history and cutting-edge of computing.

In 2023 you were recognized by the Computer History Museum for developing a Linux supercomputer using commodity hardware. Your approach is now the dominant method in high-performance computing. Was that a life-shaping lesson for you in not being afraid to try unconventional things? How do you explain this lesson to your students?

Certainly, being recognized by the Computer History Museum for my early work in developing a Linux supercomputer using commodity hardware was a pivotal moment in my career, and it underscored a fundamental lesson that has shaped not only my approach to computing but also how I mentor and teach. In the world of research and innovation, the courage to explore unconventional paths is often the key to groundbreaking discoveries. This project was a testament to that belief. At a time when the idea of assembling a supercomputer from off-the-shelf components was unconventional, I saw an opportunity to democratize access to high-performance computing. It was a venture into the unknown, leveraging the emerging potential of Linux and commodity hardware to build something that was both accessible and powerful. This experience taught me the importance of embracing risk and the value of resilience. There were technical hurdles, skepticism from peers and the daunting task of venturing beyond established norms.

Yet, it was through navigating these challenges that I not only succeeded in this immediate goal but also laid the groundwork for future advancements in high-performance computing. When I share this journey with my students, I emphasize the importance of curiosity and perseverance. I encourage them to question the status quo and to see beyond conventional wisdom. The lesson is not just about the success of the project itself but about the mindset it fostered. I stress that failure is not the opposite of success but a stepping stone towards it. The Linux supercomputer project was not just about the technology, it was about building a community around an idea.

You were recently elected to the Computing Research Association’s Board of Directors. CRA helps set academic and industrial research directions through its many activities, which include advising Congress and the National Science Foundation. What inspired you to seek this role and how do you anticipate being involved?

In my bid to join the Computing Research Association board, I’m committed to aligning the organization’s efforts with the transformative wave of the AI revolution. The CRA’s mandate extends beyond the confines of traditional computer science, encompassing the burgeoning fields of machine learning, data science and artificial intelligence. These areas are critical to the future of computing research and must be integrated into the CRA’s vision. At NJIT, we’ve established ourselves as pioneers by introducing one of the nation’s first data science academic programs and departments. This initiative exemplifies the kind of leadership and foresight I believe the CRA should embody, ensuring it remains at the forefront of data science and computing research advancements. My vision extends to nurturing the next generation of innovators and thought leaders, essential for maintaining the US’s competitive edge in technology.

A significant barrier to this goal is the inadequate Ph.D. stipends that deter many talented individuals from pursuing research careers. I advocate for doubling the standard Ph.D. stipend, making research careers more attractive and reflective of the value these roles bring to our society. Joining the Computing Research Association board represents a significant milestone and responsibility that aligns with my professional values and aspirations in the field of computing research.

You’re an advocate for democratizing the power of data science and supercomputing. How does the rise of user-friendly artificial intelligence systems such as ChatGPT impact your work? How does it impact the overall work of the Institute for Data Science?

Absolutely, the rise of user-friendly artificial intelligence systems like ChatGPT marks a pivotal moment in our pursuit to democratize data science and supercomputing. For my work, this evolution serves as both a tool and a testament to the power of making complex computational capabilities accessible to a broader audience. It enriches the palette of methodologies and technologies at our disposal, enabling us to tackle more ambitious projects with greater efficiency and creativity. By integrating these AI systems into our research and educational programs, we’re not just enhancing our ability to process and analyze data, we’re also empowering students and researchers with the means to innovate and explore new horizons in data science without being hindered by the technical complexities that once acted as barriers. For the Institute for Data Science, the impact of such AI systems is transformative. They serve as a bridge between advanced computational technologies and a diverse range of disciplinary domains, facilitating interdisciplinary research and collaboration.

A lot of people who are information workers are afraid that AI will make their careers obsolete. Technology progress can’t be stopped, so how should people adapt?

In the face of technological progress, particularly with the rapid advancement of AI, it’s understandable that information workers may feel apprehensive about the future of their careers. However, rather than viewing AI as a harbinger of obsolescence, it’s crucial to see it as a catalyst for evolution and innovation in our work practices. The key to adapting is in embracing these technologies, learning to work alongside them, and leveraging their capabilities to enhance our own skill sets and productivity. The first step in this adaptation process is to cultivate a mindset of lifelong learning. As AI and other technologies continue to evolve, so too must our skills and knowledge. This means staying informed about new technologies, seeking out educational opportunities, and being open to acquiring new competencies that complement the capabilities of AI.

For instance, developing skills in data literacy, AI ethics, and understanding the principles of machine learning can make workers more versatile and valuable in an AI-integrated workplace. Additionally, it’s important to focus on the uniquely human skills that AI cannot replicate, such as creativity, emotional intelligence, and critical thinking. By honing these abilities, workers can ensure they remain irreplaceable components of the workforce, capable of tasks that require a human touch, from complex decision-making to empathetic interactions with customers or clients.

Other than creative prompt-making, what should non-programmers learn now about AI?

For non-programmers looking to delve deeper into AI, understanding the ethical implications and societal impacts of AI is paramount. It’s important to be aware of how AI decisions are made, the potential biases in AI systems, and the ethical considerations of AI use. Additionally, developing data literacy is crucial, as it enables individuals to evaluate AI outputs and understand the importance of data quality and biases. A basic grasp of AI and machine learning concepts, even without programming skills, can demystify AI technologies and reveal their potential applications. Staying informed about AI advancements across various sectors can also inspire innovative ideas and foster interdisciplinary collaborations. By focusing on these areas, non-programmers can contribute meaningfully to the AI conversation and its future direction.

There’s a popular sci-fi plot where the computers get so smart that people lose control. The new class of user-friendly AI is certainly making people excited but also nervous. Should we be afraid?

The emergence of user-friendly AI technologies has indeed brought this conversation into the mainstream, highlighting the balance we must strike between harnessing the benefits of AI and addressing valid concerns about its implications. It’s critical to recognize that the AI technologies we’re creating today are built with numerous safeguards, are subject to ethical guidelines, and operate within evolving regulatory environments. These measures are designed to ensure AI systems augment human abilities and decision-making, rather than supplanting or undermining human control.

While it’s natural to harbor concerns about the rapid progression of AI, allowing fear to dominate the discourse would be a disservice to the potential benefits these technologies can offer. Instead, this moment calls for proactive engagement with AI, an investment in understanding its inner workings, limitations, and the ethical dilemmas it presents. By advocating for responsible AI development, emphasizing education, and promoting transparency, we can foster an environment where AI serves as a tool for societal advancement. This approach ensures that we remain at the helm of AI’s trajectory, steering it towards outcomes that uplift humanity rather than scenarios that fuel dystopian fears.

Other than AI, which emerging technologies excite you the most right now in terms of their potential to transform computing?

In the realm of computing, beyond the transformative power of AI, quantum computing stands out as an especially exciting frontier. This technology, with its potential to solve complex problems exponentially faster than classical computers, could revolutionize fields ranging from cryptography to drug discovery, climate modeling, and beyond. Quantum computing’s promise to tackle challenges currently beyond our reach, due to its fundamentally different approach to processing information, represents a leap forward in our computational capabilities. Its convergence with AI could lead to unprecedented advancements, making this era an incredibly thrilling time to be at the forefront of computing and data science.

https://news.njit.edu/njits-david-bader-future-ai-silver-linings-touch-grey