Human-AI Interaction design is perhaps the most important of these new developments. It is a process, one that requires a deep understanding of people. It starts with observations and then a rigorous attempt to use those observations to determine the true underlying issues and needs, a process that might be called “Problem Defining” (as opposed to problem solving). Then, these needs and issues are addressed through an iterative, evidence-based procedure of observation, ideation, prototyping, and testing, with each cycle of the iteration going deeper and deeper into the solution space. The result is a form of incremental innovation, optimizing the solution through a hill-climbing process.

The system that we all want to improve can thus be visualized as a trained human being together with your artifacts, language, and methodology. The explicit new system you contemplate will involve as artifacts computers, and computer-controlled information-storage, information-handling, and information-display devices. The aspects of the conceptual mechanism or framework that are discussed here are primarily those relating to the human being’s ability to make significant use of such equipment in an integrated system.

The autonomous writing machine, for example, would permit you to use a new way of composing text. For instance, trial drafts could rapidly be composed from re-arranged excerpts of old drafts, together with new words or passages which you stop to type in. Your ‘beta’ version could represent a free outpouring of thoughts from social media walls in any order, with the inspection of foregoing thoughts continuously stimulating new considerations and ideas to be entered. If the tangle of thoughts represented by the ‘beta’ became too complex, you would compile a reordered ‘beta’ quickly. It would be practical for you to accommodate more complexity in the trails of thought you might build in search of the path that suits your needs.

An automaton (automata or automatons), on the other hand, is a relatively self-operating machine, or control mechanism designed to automatically follow a sequence of operations, or respond to predetermined instructions. Digital operations facilitate the automation of work, allowing the work to be performed by a machine instead of a human. That machine may be a programmable mechanical device such as a robot, or a software application that performs automated tasks, known simply as a bot. In a product supply chain, automated digital operations might include automatic periodic preventive maintenance or replenishment. Amazon Prime customers can thus sign up for automatic monthly delivery of consumables like toilet paper. Computer numerically controlled (CNC) machines, such as 3D printers for additive manufacturing and digitally controlled flexible manufacturing systems (FMS), are also examples of digital automation. (Read More Here)

For most enterprises, it’s clear that the future will be autonomous. Machines will deliver services that are continuous, auto-compliant, self-healing, self-learning and self-aware. An organization’s need for greater precision decisions will require new connections to data-driven digital networks and more and more sources of data. Ultimately, the battle for public, private and shared data will shape who wins in the new networked economies that will form the future of this autonomous decade.

Over ninety percent of our world is decentralized. Humans, cars, vehicles, shops, restaurants, kitchen appliances, personal items, wallets, etc. Yet, some they are connected, integrated and re-integrated through centralized systems and platforms. This constructs what we call a multiplex networks. We face a range of complex challenges across multiple networks, including health, climate, supply chain, and transportation. These challenges require solutions that foster cooperation, promote shared prosperity, and align the interests of multiple entities. However, achieving these solutions is difficult because they require incentivization without relying on trust, knowledge sharing without centralization, and decentralized AI across data partitions. Our goal is to collaborate with other like-minded institutes such as Massachusetts Institute of Technology (see video in this series) and scale our products and services as Decentralized AI, identify the best use cases for decentralized technologies, and create new models of cooperation and collaboration. We also focus on integrating decentralized technologies with other technologies to create a more resilient, equitable, secure, and open future. Join us on this exciting journey to create a decentralized society and Web3 that positively impacts various sectors.

We’re building products, services and programs to bring together partners from across the globe, including open source communities, technology companies, non-profits, local, state, and federal governments, as well as researchers in academia and industry.

The program currently focuses on three emerging areas:

• Digitalization of Banknotes
• Decentralized AI
• Computational Privacy and Security

The program will support several scientists and researchers. The activities of the program span several areas:

• Research in the three pillars with an emphasis on responsible innovation and shared prosperity
• Shared open-source standards and code bases and data sets
• APIs, standards, and case studies in the emerging areas
• Roundtable meetings with stakeholders and special events
• Fostering an entrepreneurial ecosystem including researchers, start-ups, and corporate ventures