Collaborative intelligence characterizes multi-agent, distributed systems where each agent, human or machine, is autonomously contributing to a problem solving network.
The successes of small open source experiments in generative AI provide a model for a paradigm shift from centralized, hierarchical control to decentralized bottom-up, evolutionary development.
[8] A key application domain for collaborative intelligence is risk management, where preemption is an anticipatory action taken to secure first-options in maximising future gain and/or minimising loss.
In the late 1980s, Eshel Ben-Jacob began to study bacterial self-organization, believing that bacteria hold the key to understanding larger biological systems.
P. dendritiformis manifests a collective faculty, which could be viewed as a precursor of collaborative intelligence, the ability to switch between different morphotypes to adapt with the environment.
The vision behind this initiative was later elaborated in a Perspective in Nature Machine Intelligence,[21] which proposed a synergy between lifelong learning and the sharing of machine-learned knowledge in populations of agents.
Following are examples of crowdsourced experiments with attributes of collaborative intelligence: As crowdsourcing evolves from basic pattern recognition tasks to toward collaborative intelligence, tapping the unique expertise of individual contributors in social networks, constraints guide evolution toward increased functional effectiveness, co-evolving with systems to tag, credit, time-stamp, and sort content.
Research by Dror Y. Kenett and his Ph.D. supervisor Eshel Ben-Jacob uncovered hidden information about the underlying structure of the U.S. stock market that was not present in the standard correlation networks, and published their findings in 2011.
[32] Collaborative intelligence addresses problems where individual expertise, potentially conflicting priorities of stakeholders, and different interpretations of diverse experts are critical for problem-solving.
Potential future applications include: Wikipedia, one of the most popular websites on the Internet, is an exemplar of an innovation network manifesting distributed collaborative intelligence that illustrates principles for experimental business laboratories and start-up accelerators.
[33] A new generation of tools to support collaborative intelligence is poised to evolve from crowdsourcing platforms, recommender systems, and evolutionary computation.
[25] Existing tools to facilitate group problem-solving include collaborative groupware, synchronous conferencing technologies such as instant messaging, online chat, and shared white boards, which are complemented by asynchronous messaging like electronic mail, threaded, moderated discussion forums, web logs, and group Wikis.