By now, plenty of us know that artificially intelligent virtual assistants like OpenAI's ChatGPT and Google's Bard can pull off sensational stunts, such as winning coding contests, passing bar exams and professing love to a tech columnist. But I wondered: How helpful are the bots, really, as actual assistants? Older A.I. bots like Apple's Siri and Amazon's Alexa had more than a decade to improve, but they ended up stagnating and are now used mostly for setting timers and playing music. ChatGPT and Bard, on the other hand, use so-called large language models that recognize and generate text based on enormous data sets scraped off the web. They are trained to compose sentences on the fly as if they were human, which potentially makes them far more versatile as assistants.

We are all witnessing the evolution of Virtual Assistants towards replacing the Executive Assistant's duties, and it's time to ask ourselves a question: what's beyond that? Imagine yourself in 10 years working in a team, how does your day look like? What are the mundane tasks you won't be doing anymore? What are the tasks you will be focusing on? I did that exercise a few times, and needless to say, among the currently emerging technology trends, I believe Artificial Intelligence (AI) will have the biggest impact on our lives.

Executive secretaries are in roles critical to the organizations and executives they serve. Indeed, the role can also be quite fluid – extending to encompass chief operating officer, internal communications, HR, learning and development, special projects, and corporate troubleshooting. Given this wide-ranging remit, we believe executive assistants are on the front lines of the exponential changes happening in the business world. Now, perhaps more than ever, they need to understand the forces of change shaping the future and the range of ways these could impact their own roles and shape the challenges and choices facing the organisations and executives they work with. Secretaries have wielded a number of tools over the decades, from telegraphs, to telephones, to personal computers to, now, personal digital assistants.

How did you end up working in Information and Data Sciences at Microsoft Research? Paul Bennett: I started quite a while ago. Originally looking first at just philosophical problems of how we reason about things.

Articles about artificial intelligence often begin with an intention to shock readers, referencing classic works of science fiction or alarming statistics about impending job losses. But I think we get closer to the heart of AI in 2018 when we think about small and mundane ways in which AI makes work just a little easier. And it's not necessarily the AI experts in your organization who will identify these mundane problems that AI can help solve. Instead, employees throughout the organization will be able to spot the low-hanging fruit where AI could make your organization more efficient. But, only if they know what AI is capable of doing, and what it should never do.

If you're an Executive Assistant, I'd say you've got 2 good years left to do your job in the same manner you've always done it. For those of you who think that Executive Assistants are so "specialized" and "unique" that they could never be replaced, please allow me to lovingly slap you across the face. Our role has historically been one that does the most, but garners the least amount of respect within the organization. Shit, we still have issues walking into our Exec's office and demanding pay commensurate with the work that we actually do and all of the miracles we perform on a daily basis! We can't even advocate for ourselves 90% of the time, yet we feel we're somehow indispensable "because soft skills."

This presentation provides an initial conceptual framework for "Understanding Cognitive Systems" – this presentation can be downloaded from slideshare.net/spohrer I'm Jim Spohrer, I work at IBM and I am the presenter, and in today's short talk, I will briefly cover what is a cognitive system (entity) – both biological and digital. Then I will briefly discuss how to build, understand, and work with digital cognitive systems – and how this is steps towards a next generation cognitive curriculum, including types of digital cognitive systems. Biological cognitive system entities… and human intelligence… The best explanation of what a biological cognitive system entity is can be found in Terrence Deacon's book- the Symbolic Species – the co-evolution of language and the brain. All easily recognizable biological cognitive systems from ants to wolves to crows to dolphins to monkeys to people have brains that have co-evolved with symbol systems - chemical, visual, auditory – that individuals of the species you as a type of language for communicating and coordinating reasoning and interactions and the accumulation of knowledge for successful multi-generational living in an environment. Less sophisticated languages and brains deal primarily with the physical world, but more sophisticated languages and brains are needed to deal with the social and in the case of people, the cultural and institutional world, of large numbers of others of their species living in close proximity with each other.