Artificial intelligence is all the rage today. Unfortunately, people treat it as a cool new fad to jump on without realizing the massive impact AI has today. But the future of AI will demand our attention in how we work and what our expectations will be.
Further, AI will become more than a tool in a newfangled tech toolbelt. Think of collaborative AI as your new digital assistant that you can talk to, interact with, and will understand your native language. Mind-blowing? For sure, but this is just the tip of the iceberg.
So, where do we go from here? To help me understand the future of collaborative AI and its impact on humans and how we work is Aleksandra Przegalinska. She is the Vice Rector at Kozminski University, Research Fellow for the American Institute for Economic Research, and a frequent speaker and contributor to the AI Community of SwissCognitive.
01:50 — With her recent research, Aleksandra received a grant for her work with AI. The first part involves collaborative AI and how AI should be an extension of what we do—to support and collaborate with humans, not to replace what we can do.
03:01 — For the second part of the grant, they are using conversation AI systems and further developing based on new types of algorithms and neural networks. These systems, called ‘transformers,’ go beyond the functions of a simple chatbot. For instance, with human supervision, transformers can write short stories or blog posts and translate texts in a contextual way.
05:31 — The advancement of these neural networks introduces new possibilities of delivering clear speech synthesis and a more granular understanding of word pronunciations and meanings. Because of this, transformers will be able to serve as an assistant that understands what you’re saying and your intentions with a specific context.
07:58 — There are many companies trying to democratize AI to make it easier to build upon, such as with low-code/no-code and citizen developers. There are those who understand the deep technical aspect of AI. On the other hand, there are people still trying to understand it, use it, and learn about this technology. How can we bridge the gap between this divide?
10:10 — By democratizing AI, it will be more accessible and more people will be able to benefit from it. Now is a good time for AI simplification as well as AI complexity.
16:22 — A lot revolving around AI involves the collaboration of people and ideas. How can collaborative AI be used?
17:30 — Collaboration with humans requires advanced neural networks. Additionally, the system would have to adapt to the pace that a human works. The idea is essentially to create human-centric systems that can either do something with humans or complete the part of a task that contributes to a bigger solution designed by humans.
19:53 — During the Industry Cloud Battleground digital event, a manufacturing session mentioned the emergence of micro-factories using a combination of IoT, AI, and other technologies to streamline output.
21:03 — On the retail side, people are repurposing shipping containers to create mini-stores to bring the retail experience to events and farmers’ markets. These retailers use AI and analysis to determine what products to bring based on the customers at the events. This requires contextual understanding and translating the digital into the physical.
21:54 — Collaborative AI is on the horizon. There will be more applications of specialized AI in different domains and sectors. There can’t be a generic approach to AI—it has to be specialized, but it relies on specialists within each industry to adopt it and provide feedback for improvements.
23:49 — With the lines blurring between industries, there also needs to be AI collaboration with other AI components.
24:54 — Transformers are an example of the future of AI, as these systems continue to advance with contextual and conversational AI. Also, specialists should explore the possibilities of AI within their specific industries, as it serves as a useful assistant and tool to enhance various domains.