What are computers for?
Historical Visions of Computing
Historically, different answers to this question – different visions of computing – have helped inspire and determine the computing systems humanity has ultimately built. Consider the early electronic computers. ENIAC, the world’s first general-purpose electronic computer, was commissioned to compute artillery firing tables for the United States Army. Other early computers were also used to solve numerical problems, such as simulating nuclear explosions, predicting the weather, and planning the motion of rockets. The machines operated in a batch mode, using crude input and output devices, and without any real-time interaction. It was a vision of computers as number-crunching machines, used to speed up calculations that would formerly have taken weeks, months, or more for a team of humans.
The Vision of Augmenting Human Intelligence
In the 1950s, a different vision of what computers are for began to develop. That vision was crystallized in 1962, when Douglas Engelbart proposed that computers could be used as a way of augmenting human intellect. In this view, computers weren’t primarily tools for solving number-crunching problems. Rather, they were real-time interactive systems, with rich inputs and outputs, that humans could work with to support and expand their own problem-solving process. This vision of intelligence augmentation (IA) deeply influenced many others, including researchers such as Alan Kay at Xerox PARC, entrepreneurs such as Steve Jobs at Apple, and led to many of the key ideas of modern computing systems. Its ideas have also deeply influenced digital art and music, and fields such as interaction design, data visualization, computational creativity, and human-computer interaction.
Artificial Intelligence Augmentation (AIA)
Research on IA has often been in competition with research on artificial intelligence (AI): competition for funding, competition for the interest of talented researchers. Although there has always been overlap between the fields, IA has typically focused on building systems which put humans and machines to work together, while AI has focused on complete outsourcing of intellectual tasks to machines. In particular, problems in AI are often framed in terms of matching or surpassing human performance: beating humans at chess or Go; learning to recognize speech and images or translate language as well as humans; and so on.
Artificial Intelligence Augmentation (AIA)
This essay describes a new field, emerging today out of a synthesis of AI and IA. For this field, we suggest the name artificial intelligence augmentation (AIA): the use of AI systems to help develop new methods for intelligence augmentation. This new field introduces important new fundamental questions, questions not associated with either parent field. We believe the principles and systems of AIA will be radically different from most existing systems.
Using Generative Models to Invent Meaningful Creative Operations
Our essay begins with a survey of recent technical work hinting at artificial intelligence augmentation, including work on generative interfaces – that is, interfaces which can be used to explore and visualize generative machine learning models. Such interfaces develop a kind of cartography of generative models, ways for humans to explore and make meaning from those models, and to incorporate what those models "know" into their creative work.
Conclusion
It is conventional wisdom that AI will change how we interact with computers. Unfortunately, many in the AI community greatly underestimate the depth of interface design, often regarding it as a simple problem, mostly about making things pretty or easy-to-use. In this view, interface design is a problem to be handed off to others, while the hard work is to train some machine learning system.
This view is incorrect. At its deepest, interface design means developing the fundamental primitives human beings think and create with. This is a problem whose intellectual genesis goes back to the inventors of the alphabet, of cartography, and of musical notation, as well as modern giants such as Descartes, Playfair, Feynman, Engelbart, and Kay. It is one of the hardest, most important, and most fundamental problems humanity grapples with.
Frequently Asked Questions
Q: What is the main idea of this essay?
A: The main idea is that artificial intelligence can be used to augment human intelligence, not just to replace it.
Q: What is the difference between AI and IA?
A: AI is focused on building systems that can perform tasks that typically require human-level intelligence, such as recognizing faces or understanding language. IA, on the other hand, is focused on building systems that can work in conjunction with humans to perform tasks that require human creativity, intuition, and judgment.
Q: What is the goal of AIA?
A: The goal of AIA is to use AI systems to help develop new methods for intelligence augmentation, which can lead to new forms of creativity, inspiration, and innovation.
Q: How does AIA differ from AI?
A: AIA differs from AI in that it focuses on building systems that can work in conjunction with humans, rather than replacing them. It also focuses on developing new forms of creativity, inspiration, and innovation, rather than just improving performance on specific tasks.
Q: What are the potential benefits of AIA?
A: The potential benefits of AIA include new forms of creativity, inspiration, and innovation, as well as new ways of working and collaborating with machines.
