Engaging AI Topics, and Videos, to Explore During Your Academic Winter Break | 2024
<Update> 10 December, to reflect Google’s unveiling of their Quantum computer processor
The Rise of AI Ubiquity
AI has already transitioned from a buzzword to a pervasive reality. From recommendation systems that tailor our online experiences to generative models capable of producing art, music, and the occasional paragarph in a term paper, AI’s influence is both vast and granular. In academics, it still serves as a constant reminder of how we, as educators, need to rethink and reshape what we assess for student learning. And yet, the consumer grade accessible AIs still seems novel, or in the case of writing, made of empty calories. So, what makes this artificiality look “intelligent” anyway?
AI: Promise and Peril
The interplay between the promises and dangers of AI underscores its massive upside while revealing the challenges we face in wielding it. AI’s ability to process data at what we perceive as near-instantaneous speeds offers huge benefits in fields like public safety and automation. Think self-driving cars that could virtually eliminate traffic accidents or healthcare systems that prevent critical medical errors while optimizing emergency responses. But, with all this progress comes a darker side. The same technology enabling these breakthroughs also fuels ethical concerns about privacy and government overreach. AI-powered surveillance can track behavior in real-time, predict actions, and even influence populations—a scenario straight out of a Sci-Fi thriller like Skynet (but without the bombs, yet). The difference is that what once seemed like a distant fiction feels uncomfortably close for some, as the tech we fantasized about in books and movies starts to shape our everyday reality as I reach for my iPhone to ask Siri to reword this sentence for me.
Instead of fearing what AI could do, we need to focus on finding a balance—harnessing its potential for societal good while safeguarding individual freedoms. Achieving this balance will require robust ethical frameworks and transparent policies, ensuring these systems are equitable and accountable. But in academia, whether we like it or not, we are at the forefront of this transformation. It’s our students who will live with, and shape, the policies that govern AI technologies. The key for us is teaching and integrating AI literacy into their education. This goes beyond its fun, surface-level applications like generating blog visuals or drafting the occasional response in Canvas. It’s about equipping students with the critical skills to understand, evaluate, and engage with AI’s ethical, societal, and technical implications; along with its practical usage.
A Future Synergy
AI’s march toward ubiquity is fueled by advancements in deep learning, natural language processing, and new forms of inputs. These systems are still running on the concept of 1’s and 0’s, providing the illusion that computers can “create” at breakneck speeds. Yet, we are only in the dial-up days of AI.
It is apparent that soon, every device, from traffic systems to wearable health monitors, will operate with some kind of AI influence. And with it, new policy and ethical debates, process and protocols, will have to be discusses and implemented to keep from what sci-fi has pegged AI as for years; the dystopian descent of humankind.
On the fringe of this space, what is also being invested in and investigated is the idea of Quantum computing. The ability to not rely on computer interfacing with just 1’s and 0’s, but both at the same time. In theory, it will break open computing to an entirely new level, and with AI, it has the potential to reshape what humans can do with technology.
Quantum Computing: The Accelerator
AI is advancing rapidly, driven by breakthroughs in deep learning and natural language processing. But we’re still in the early stages, think dial-up internet days. Soon, AI will touch everything, from traffic systems to wearable health devices, creating new ethical and policy challenges that must be addressed to prevent the dystopian outcomes often depicted in sci-fi.
On the fringe edge of the AI discussion, or debate, is quantum computing, which moves beyond the traditional binary system of 1’s and 0’s. Quantum computers use qubits and superposition to perform calculations at speeds and complexities that classical computers can’t even approach. This could fundamentally reshape how we solve problems, from breaking encryption to potentially curing diseases by simulating molecular structures. While this is still decades away, the U.S. and China are already in a race to develop these technologies.
IBM, often overlooked in Silicon Valley’s spotlight, is one of the key players leading the charge in quantum research.
Ultimately, it’s not a matter of if AI and quantum computing will change the world, but when—and as Moore’s law has shown in our technology past, our future is just compounding closer as we speak.