Autonomous Chess Robot; A Risk Assessment of the Quantum Threat
Cooney, Nick, School of Engineering and Applied Science, University of Virginia
Powell, Harry, EN-Elec & Comp Engr Dept, University of Virginia
Wayland, Kent, EN-Engineering and Society, University of Virginia
Originating in India in the 7th century A.D., chess is a complex strategy game in which two opposing forces contest to capture their adversary’s "king". Since its creation, the technological world has inspired interest in automating the sport to allow for single-user gameplay. The most notable outcome of these efforts was the development of chess engines, which are systems capable of engaging in a complete game of chess. However, while a chess engine is capable of generating and analyzing moves, it still requires a human operator to physically relocate its pieces around the board, thereby failing to achieve true autonomy. To address this need, a robot was designed and built to play an intelligent, over-the-board game of chess, against a human opponent, with no intervention from a human operator.
The design utilized a three-axis, cantilevered, overhead gantry as its frame, which allowed for movement parallel to a chess board. Each axis was driven by a stepper motor, with the horizontal axes using belts and the vertical axis using a rack and pinion. An electromagnet at the end of the vertical axis’s rack allowed the robot to retrieve and move the chess pieces, which had been outfitted with magnets on their bases and metal plates on their tops. An electromechanical sensor network embedded within the board allowed the system to detect pieces based on the locations of their base magnets. The system was orchestrated by an MSP432E401Y microcontroller, which interfaced to the motors and sensor network through a custom printed circuit board. The open-source Stockfish chess engine was used for move generation on a separate single-board computer, the Raspberry Pi 3A+. The system’s performance was evaluated based on speed, accuracy, correctness, level of play, and sensor accuracy. Results were collected across three hours of continuous gameplay by random participants. In this time, the robot achieved maximum scores for speed, correctness, and level of play, by taking less than ten seconds per move, never performing an incorrect move, and handling all move types (ordinary moves, captures, promotions, castling, and en passant). Unfortunately, the robot only achieved 97% sensor accuracy, resulting from a misstep in the early design process whereby directional sensors were selected. This was easily corrected during the testing process by manually rotating the chess pieces whenever the sensors failed. Future work should seek to address this shortcoming with non-directional, proximity-based sensors.
Being an offline system, one consideration that did not factor into the chess robot’s design was online security. Most online security is handled through asymmetric cryptosystems, which define encryption and decryption protocols for secure data transmission. The two most common asymmetric schemes in use today are the Rivest-Shamir-Adleman (RSA) cryptosystem and the Elliptic Curve Digital Signature Algorithm (ECDSA) cryptosystem. The security of RSA and ECDSA rely on the difficulty of solving two classes of computational problems, the integer factorization problem (IFP) and the discrete logarithm problem (DLP), respectively. However, in 1997, mathematician Peter Shor developed algorithms that he proved capable of efficiently solving both the IFP and DLP. The shortcoming of Shor’s algorithms were that they can only be run on a device known as a "quantum computer", the hardware for which does not yet exist. Therefore, as soon as quantum hardware capable of executing Shor’s algorithms becomes viable, much of the world’s online security infrastructure will become vulnerable to cyberattacks. Such a scenario is called a "quantum threat".
Unfortunately, there is a growing divide between quantum computing experts, who understand the current state of the technology, and the public, who are interested in the potential risk of quantum computing to society. To bridge this divide, a series of interviews were conducted with quantum computing experts to better communicate the current state of quantum technology to the public. Ideally, this will allow the public to engage in informed debate prior to the occurrence of a quantum threat scenario. Results from each expert interview were analyzed through the lens of risk assessment, which considers the sociotechnical factors that affect risk perception and communication in the interest of mitigation. This analysis showed that the prevention of a quantum threat scenario requires a joint effort from industry, government, and the public. It is crucial that industry and government begin implementing post-quantum cryptography (PQC) protocols immediately. However, the public is responsible for carefully evaluating which organizations deserve their trust, and pushing the world to prioritize the transition to PQC protocols. While the public should not live in fear of a quantum threat scenario, it is important to realize that quantum computing is a complex field, both in theory and application. Experts must work to properly assess and communicate risks to the public to prevent unnecessary fear, and the public must situate their perception of risk in the context of a growing quantum landscape. Only with the combined efforts of industry, government, and the public will it be possible to bridge the quantum divide and avoid fallout from a quantum threat scenario. It is worth noting that the experts involved in this process were predominately focused on quantum computing from the viewpoint of industry. Future work should seek to better include the viewpoints of academia and research.
BS (Bachelor of Science)
autonomous, chess, robot, quantum computing, quantum threat, quantum divide, cryptography, risk assessment
School of Engineering and Applied Science
Bachelor of Science in Computer Engineering
Technical Advisor: Harry Powell
STS Advisor: Kent Wayland
Technical Team Members: Keenan Alchaar, Eli Jelesko, Gabriela Portillo