Hybrid-intelligence interfaces optimally exploit the best of human and machine intelligence

Researchers developed a versatile remote gaming interface that allowed external experts as well as hundreds of citizen scientists all over the world through multiplayer collaboration and in real time to optimize a quantum gas experiment in a lab at Aarhus University.

Surprisingly, both teams quickly used the interface to dramatically improve upon the previous best solutions established after months of careful experimental optimization. Comparing domain experts, algorithms and citizen scientists is a first step towards unravelling how humans solve complex, natural science problems.

In a future characterized by algorithms with ever increasing computational power, it becomes essential to understand the difference between human and machine intelligence. This will enable the development of hybrid-intelligence interfaces that optimally exploit the best of both worlds. By making complex research challenges available for contribution by the general public, citizen science does exactly this. Numerous citizen science projects have shown that humans can compete with state-of-the-art algorithms in terms of solving complex, natural science problems.

However, these projects have so far not addressed why a collective of citizen scientists can solve such complex problems. An interdisciplinary team of researchers from Aarhus University, Ulm University, and the University of Sussex, Brighton have now taken important first steps in this direction by analyzing the performance and search strategy of both a state-of-the-art computer algorithm and citizen scientists in their real-time optimization of an experimental laboratory setting.

The Alice Challenge 

In the ‘Alice Challenge’, Robert Heck and colleagues gave both experts and citizen scientists live access to their ultra-cold quantum gas experiment. This was made possible by using a novel remote interface created by the team at ScienceAtHome, Aarhus University. By manipulating laser beams and magnetic fields, the task was to cool as many atoms as possible down to extremely cold temperatures just above absolute zero at -273.15°C. This so-called Bose-Einstein condensate (BEC) is a distinct state of matter (like solid, liquid, gas or plasma) that constitutes an ideal candidate for performing e.g. quantum simulation experiments and high precision measurements.

As detailed below both groups successfully used the remote interface to improve on previously optimal solutions. In this first ever citizen science experimental optimization challenge with real-time feedback the researchers further quantified the behavior of citizen scientists. They concluded that what makes human problem solving unique is how a collective of individuals balance innovative attempts and refine existing solutions based on their previous performance.

Quantum optimization as a remote service

Quantum technology is increasingly stepping out of university labs and into the corporate world. For high-performance and robust applications exceptional levels of control of the complex systems is needed and new methodologies in both theoretical and experimental science are needed.

This requires interdisciplinary and often trans-institutional collaborations, which in turn necessitates the development of efficient interfaces to allow each of the experts to contribute as efficiently as possible.

In recent years, remote interfaces to experimental apparatuses have started to appear, however, they are always focused either on educational settings or the investigation of a very particular experimental setup.

In contrast, Robert Heck and colleagues in the current work set out to develop a flexible remote interface and a powerful optimization algorithm that can potentially be applied to many other settings in the future. The experimental production of BECs serves as an ideal test-bench:

The RedCRAB package

“Making machines play the Alice Challenge alongside with humans over the internet required us to create a new software package, RedCRAB, for remote optimization of quantum experiments,” explained Tommaso Calarco (Forschungszentrum Jülich/University of Cologne) and Simone Montangero (Padova University), leaders of the Ulm optimization team.

RedCRAB is ideally suited for problems with many control parameters where the exact theoretical modelling of the system is unknown and other traditional optimization methods fail. It furthermore has the advantage that the optimization experts can easily adjust algorithmic parameters and exploit its full potential without requiring intermediate communication with the experimental team. Moreover, the efficiency of the optimization can be analyzed, and based on that, algorithmic improvements can be made and easily transferred to future experiments.

Tommaso Calarco is extremely excited about the results:

“RedCRAB optimization worked so well that it is now applied in several labs around the world to enhance the performance of quantum devices. We plan to extend this as a cloud service that we believe will likely result in faster development of the theoretical understanding, of the algorithmic development and overall of quantum science and technologies.”

Can any research challenge be turned into a game?

As mentioned above, game interfaces have in recent years enabled non-experts to use their creativity and intuition to contribute to various scientific fields. In 2016, the Aarhus research group reported the results of the first quantum citizen science game, Quantum Moves, in Nature. In the game, the players contributed to finding fast and efficient solutions to atomic transport in a quantum computing architecture.

The clear water-like analogy of that particular game and the scarcity of other quantum games has since sparked the criticism that perhaps non-experts can only contribute in research topics for which a clear classical analogy can be established. Since this can rarely be established for any given research challenge, it could seem that the gamification approach is of very limited general applicability and Quantum Moves was just a very special case.

Game interface of the Alice Challenge. Players could manipulate three curves representing two laser beam intensities and the strength of a magnetic field gradient, respectively. The chosen curves were then realized in the laboratory in real-time. Graphics: Robert Heck