Whenever humans use tools human performance is enhanced. Cognitive systems are a new kind of tool continually increasing in cognitive capability and are now performing high level cognitive tasks previously thought to be explicitly human. Usage of such tools, known as cogs, are expected to result in ever increasing levels of human cognitive augmentation. In a human cog ensemble, a cooperative, peer to peer, and collaborative dialog between a human and a cognitive system, human cognitive capability is augmented as a result of the interaction. The human cog ensemble is therefore able to achieve more than just the human or the cog working alone. This article presents results from two studies designed to measure the effect information supplied by a cog has on cognitive accuracy, the ability to produce the correct result, and cognitive precision, the propensity to produce only the correct result. Both cognitive accuracy and cognitive precision are shown to be increased by information of different types (policies and rules, examples, and suggestions) and with different kinds of problems (inventive problem solving and puzzles). Similar effects shown in other studies are compared.

A computer mouse that inspired Steve Jobs to create Apple's first mice has clicked with bidders at a $178,936 (£147,000) auction. The early mouse and coding keyset was created by computing legend Douglas Engelbart, a pioneer of the controller system. The lot sold for approximately 12 times its estimate of $14,640 (£12,000) in a sale by Boston-based RR Auction on Thursday. The rare, early three-button computer mouse designed by Engelbart utilises two metal discs which correspond to the X-axis and Y-axis on the bottom to locate the position of the cursor, rather than a ball or optical light that came to be used later. The coding keyset, features five keys, permitting 31 key-press combinations, for typing and entering commands.

We will soon be surrounded by artificial systems capable of cognitive performance rivaling or exceeding a human expert in specific domains of discourse. However, these "cogs" need not be capable of full general artificial intelligence nor able to function in a stand-alone manner. Instead, cogs and humans will work together in collaboration each compensating for the weaknesses of the other and together achieve synthetic expertise as an ensemble. This paper reviews the nature of expertise, the Expertise Level to describe the skills required of an expert, and knowledge stores required by an expert. By collaboration, cogs augment human cognitive ability in a human/cog ensemble. This paper introduces six Levels of Cognitive Augmentation to describe the balance of cognitive processing in the human/cog ensemble. Because these cogs will be available to the mass market via common devices and inexpensive applications, they will lead to the Democratization of Expertise and a new cognitive systems era promising to change how we live, work, and play. The future will belong to those best able to communicate, coordinate, and collaborate with cognitive systems.

During the fall of 2000 I visited the Special Collection room in Green Library at Stanford University, eager to read Stewart Brand's personal journals. I was researching the political and cultural world surrounding three computer science laboratories that were located adjacent to Stanford during the decade during which the technologies that led to the creation of the personal computer industry and the modern Internet emerged. On my initial visit I came away disappointed and it would take almost another two decades before I discovered a missing piece of the puzzle that reframes the early history and impact of Silicon Valley. Although he was not a technologist, Brand, the creator of the Whole Earth Catalog, is an intriguing figure in the history of the modern computing world and the Valley. He was the author of a seminal article in Rolling Stone magazine, "Space War: Fanatic Life and Symbolic Death Among the Computer Bums," which had been the first hint a wider non-technical audience had of the emerging digital world.

Around the same time that Alan Turing was shaping his theories of machine intelligence in Manchester, another future giant of the computing world, Douglas Engelbart, was developing an alternative computing paradigm over 5,000 miles away in the Bay Area. Engelbart believed that computers, with their ability to synthesize and manipulate vast quantities of information, should help humans solve problems, rather than remove them from the problem-solving loop. This ideology is now known as augmented intelligence. Engelbart's contributions to the field (both as a PhD student at UC Berkeley and at SRI in the decades after) were perhaps best exemplified through "The Mother of All Demos" in 1968, where he unveiled for the first time many of the computing features we now take for granted -- the mouse, GUIs, hyperlinks, word processing, version control, and even video conferencing -- in a single demonstration. Although it's enticing to think about artificial intelligence passing human equivalency tests like Turing's Imitation Game (or maybe something more sophisticated for today's generalist AI models), we really should be thinking about how Engelbart's ideas translate to our modern AI era. Put another way, how do we build the next Mother of All Demos?

I have written about text in its digital form in the past and I would like to revisit this topic once more. J.C.R. Licklider and Douglas Engelbart were two giants who saw non-numeric possibilities in networked computing well ahead of many others. Vannevar Bush and Ted Nelson are two others who resonated with the idea of machines that assisted in the production and discovery of information. Sir Tim Berners-Lee amplified some of these ideas with the invention of the World Wide Web. Following along this path is Frode Hegland, a protegé of the late Douglas Engelbart, who has developed new tools for the production of and interaction with text. Engelbart's oNLine System (NLS)a was a tour-de-force example of disciplined use of structure to guide the production and consumption of computer-based text.

A long time ago in an innovation ecosystem far, far away… a recent MIT graduate started his career in a vintage 1970's Massachusetts Route 128 Artificial Intelligence (AI) startup doing speech recognition, re-named Verbex after Exxon acquired the company. Fast forward to AI in 2019, and what stands out most to that grad (me) are two pleasant surprises. The first surprise is the degree to which highly competitive IT businesses have embraced open source AI. Google's TensorFlow has over 120,000 stars on GitHub, which the largest home of open source code communities, and Microsoft acquired GitHub in 2018. Facebook's PyTorch is also quite popular, especially in academic and industrial research communities, with over 25,000 stars on GitHub.

Steve Jobs was fond of saying that the key to Apple's success has been a marriage of technology and the liberal arts. What he meant by this is that innovation emerges at the intersection of art and technology– rather than either alone. In fact, it was Douglas Engelbart who first understood the importance of computer technologies in bootstrapping human capabilities and augmenting human creativity. Building on Engelbart's thinking, we need to begin to better comprehend the challenges of machine intelligence in the context of human creativity and innovation-- particularly with regard to our systems of learning and education. Since its inception some sixty years ago, artificial intelligence (AI) has evolved from an arcane academic field into a powerful driver of social and economic change.

Fifty years ago last Sunday, a computer engineer named Douglas Engelbart gave a live demonstration in San Francisco that changed the computer industry and, indirectly, the world. In the auditorium, several hundred entranced geeks watched as he used something called a "mouse" and a special keypad to manipulate structured documents and showed how people in different physical locations could work collaboratively on shared files, online. It was, said Steven Levy, a tech historian who was present, "the mother of all demos". "As windows open and shut and their contents reshuffled," he wrote, "the audience stared into the maw of cyberspace. Engelbart, with a no-hands mic, talked them through, a calm voice from Mission Control as the truly final frontier whizzed before their eyes."

Doug Engelbart was the first to actually build a computer that might seem familiar to us, today. He came to Silicon Valley after a stint in the Navy as a radar technician during World War II. Engelbart was, in his own estimation, a "naïve drifter," but something about the Valley inspired him to think big. Engelbart's idea was that computers of the future should be optimized for human needs--communication and collaboration. Computers, he reasoned, should have keyboards and screens instead of punch cards and printouts. They should augment rather than replace the human intellect. And so he pulled a team together and built a working prototype: the oN‑Line System. It was a general‑purpose tool designed to help knowledge workers perform better and faster, and that was a controversial idea. Letting nonengineers interact directly with a computer was seen as harebrained, utopian--subversive, even.