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ACCON 2025 KEYNOTE ADDRESS<\/u><\/strong><\/span><\/p>\n Shared my views on the subject.<\/span><\/p>\n <\/p>\n The march of computing power from the mechanical Wright Flyer of 1903 to the AI-powered, quantum-enabled systems of today has revolutionised aviation by heightening efficiency, automation, and connectivity.<\/span><\/p>\n Artificial intelligence (AI) is well embedded in aircraft operations, while quantum computing (QC) is still experimental but set to change design and logistics.<\/span><\/p>\n But these developments bring with them profound safety and security threats, and need to be addressed with strong mitigation measures.<\/span><\/p>\n <\/p>\n Development of Computing Power in Aircraft<\/u><\/strong><\/span><\/p>\n Pre-Computing Period (1903\u20131950s): Mechanical and Analogue Systems<\/u><\/span><\/p>\n 1903 (Wright Flyer)<\/span>. No computing; manual operation through mechanical linkages and simple analogue instruments (e.g., compass, altimeter). Pilots relied on visual indicators.<\/span><\/p>\n 1930s\u20131940s<\/span>. Early commercial aircraft (e.g., Douglas DC-3) employed analogue instruments and ground radio beacons for navigation, with no computational processing.<\/span><\/p>\n Late 1940s<\/span>. Analogue computers, such as gyroscopic autopilots in fighter aircraft, employed vacuum tubes for simple stabilisation.<\/span><\/p>\n <\/p>\n Early Digital Computing (1950s\u20131970s): Analogue to Digital Shift<\/u><\/span><\/p>\n 1950s<\/span>. Analogue computers had stabilised but were heavy and restrictive.<\/span><\/p>\n 1960s<\/span>. Transistors allowed for digital avionics in military aircraft (e.g., F-4 Phantom) for simple navigation and radar. Commercial aircraft (e.g., Boeing 707) were still analogue-dominated.<\/span><\/p>\n Late 1960s\u20131970s<\/span>. Integrated circuits (ICs), which borrowed from the Apollo Guidance Computer, featured limited digital processing on aircraft such as the Concorde (1969) with analogue fly-by-wire.<\/span><\/p>\n <\/p>\n Digital Revolution (1980s\u20131990s): Fly-by-Wire and Glass Cockpits<\/u><\/span><\/p>\n 1980s<\/span>. Microprocessors created digital fly-by-wire (FBW) for the Airbus A320 (1987), utilising redundant processors (e.g., Intel 8086) to eliminate mechanical controls.<\/span><\/p>\n Glass Cockpits<\/span>. Aircraft such as the Boeing 767 (1982) combined flight, navigation, and engine information on CRT screens.<\/span><\/p>\n Flight Management Systems (FMS)<\/span>. In the 1980s (e.g., Honeywell FMS), these utilised 16-bit processors to automate fuel management and navigation, lessening pilot workload.<\/span><\/p>\n <\/p>\n Advanced Computing (1990s\u20132010s): Integration and Automation<\/u><\/span><\/p>\n 1990s<\/span>. PowerPC processors and GPS navigation in aircraft such as the Boeing 777 (1995) improved autopilot, diagnostics, and navigation.<\/span><\/p>\n Integrated Modular Avionics (IMA)<\/span>. The Airbus A380 (2005) integrated functions into centralised processors, enhancing efficiency.<\/span><\/p>\n Safety Systems<\/span>. TCAS and EGPWS employed 32-bit processors (about hundreds of MIPS) for real-time collision avoidance and terrain clearance.<\/span><\/p>\n <\/p>\n Current Period (2010s\u20132025): High-Performance Computing and AI<\/u><\/span><\/p>\n 2010s<\/span>. Multi-core processors (e.g., Intel\/ARM) in planes like the Boeing 787 and Airbus A350 provided real-time weather analysis, predictive maintenance, and flight optimisation.<\/span><\/p>\n ADS-B (2020)<\/span>. Mandatory GPS-based position broadcasting necessitated high processing for traffic management.<\/span><\/p>\n Integration with AI<\/span>. In 2025, AI systems (e.g., DARPA’s ALIAS, Boeing’s Loyal Wingman) will digest terabytes of sensor data for predictive maintenance, anomaly detection, and semi-autonomous flight.<\/span><\/p>\n Connectivity<\/span>. High-bandwidth onboard servers are used to handle operational and passenger data.<\/span><\/p>\n <\/p>\n Future Trends (2025 and beyond)<\/u><\/span><\/p>\n Quantum Computing.<\/span>\u00a0Research looks into QC for air traffic control and aerodynamics, with potential by the 2030s.<\/span><\/p>\n Sustainable Systems<\/span>. Electric\/hybrid aeroplanes (e.g., Airbus E-Fan X) use advanced battery management with real-time computing.<\/span><\/p>\n Autonomous Flight<\/span>. AI-based systems with GPU\/TPU accelerators handle petabytes of information for complete autonomous flight.<\/span><\/p>\n <\/p>\n Influences of AI and Quantum Computing on Civil Aviation<\/u><\/strong><\/span><\/p>\n Artificial Intelligence (AI)<\/u><\/span><\/p>\n Predictive maintenance<\/span>. AI enables the evaluation of sensor data to predict failures, which increases reliability and reduces expenses.<\/span><\/p>\n Flight optimisation<\/span>. AI improves fuel consumption by 10% and emissions by optimising routes and managing outages.<\/span><\/p>\n Autonomous Flight and Pilot Support<\/span>. AI autopilot and co-pilot technologies take care of standard functions and optimise emergency responses, decreasing pilot workload.<\/span><\/p>\n Airport Performance<\/span>. AI optimises check-in, baggage handling, and air traffic control, enhancing passenger journeys.<\/span><\/p>\n Design Innovation<\/span>. Generative AI shortens aerodynamic and material design cycles.<\/span><\/p>\n Market Expansion<\/span>. The AI aviation market is expected to expand at a 22.6% CAGR by 2030.<\/span><\/p>\n Quantum Computing (QC)<\/u><\/span><\/p>\n Advanced Simulations<\/span>. QC optimises computational fluid dynamics (CFD) and structural analysis for light, efficient airframes.<\/span><\/p>\n Operational Optimisation<\/span>. QC optimises difficult logistics issues (e.g., routing, cargo loading), potentially saving billions.<\/span><\/p>\n Sustainable Aviation<\/span>. QC simulates new materials and fuels for hybrid\/electric propulsion.<\/span><\/p>\n Future Potential<\/span>. NASA and Boeing studies suggest QC advantages by the 2030s, in spite of existing error-rate limitations.<\/span><\/p>\n Effects of Computing Progression<\/u><\/span><\/p>\n Efficiency<\/span>. FMS and route optimisation save billions in fuel costs each year.<\/span><\/p>\n Automation<\/span>. Automated takeoffs, landings, and cruise allow for a single pilot, or sometimes autonomous flight, particularly in the case of military aviation.<\/span><\/p>\n Maintenance<\/span>. Predictive maintenance, which relies on AI for the analysis of data, helps to reduce costs and delays.<\/span><\/p>\n Connectivity<\/span>. Global data routed in near real-time enhances operations and passenger services.<\/span><\/p>\n Safety<\/span>. With redundancy and real-time analysis (for example, TCAS, EGPWS), the accident rate has decreased more than 80% since the late 1970s.<\/span><\/p>\n <\/p>\n Key Air Force AI Applications<\/u><\/strong><\/span><\/p>\n Autonomous Combat Drones and Loyal Wingmen: AI-controlled UAVs, such as the U.S. Skyborg, Russia’s Okhotnik-B, and India’s CATS Warrior, conduct autonomous targeting, reconnaissance, and electronic warfare. Loyal wingmen (e.g., Boeing’s MQ-28 Ghost Bat) assist manned aircraft, minimising dangers to pilots.<\/span><\/p>\n AI-Assisted Air Combat<\/span>. AI systems, as indicated in DARPA’s AlphaDogfight Trials, outcompete human pilots in dogfights through quick decision-making and optimal tactics.<\/span><\/p>\n AI Co-Pilot Systems<\/span>. AI helps pilots with instant threat analysis, flight route optimisation, and weapons control, as in the U.S. Air Force’s ACE program.<\/span><\/p>\n Predictive Maintenance and Logistics<\/span>. Artificial intelligence systems like CBM+ allow for the prediction of equipment failure, which reduces downtime and optimises allocation of resources, leading to improved fleet readiness and lower costs.<\/span><\/p>\n Air Defence Systems<\/span>. AI allows for improved target detection and target engagement in air defence systems like Israel’s Iron Dome and Russia’s S-500 systems, allowing for a faster response to threats that are detected.<\/span><\/p>\n Electronic Warfare (EW)<\/span>. AI jams hostile radar independently, learns about threats, and defends assets against cyber and electromagnetic attacks.<\/span><\/p>\n Mission Planning<\/span>. AI processes battlefield information to produce optimal plans, dynamically realigns plans, and incorporates multi-source intelligence for data-driven decision-making.<\/span><\/p>\n Swarm Warfare<\/span>. Swarms of drones controlled by AI overwhelm defences, perform ISR, and jamming, with nations such as the U.S., China, and India developing this capability.<\/span><\/p>\n Benefits.<\/u><\/span><\/p>\n Better Decision Making<\/span>. AI manages sizeable amounts of data for real-time intelligence and speed of reaction.<\/span><\/p>\n Reduction in Pilot Workload<\/span>. Automators allow pilots to engage in tactically focused functions versus technically focused functions.<\/span><\/p>\n Improvement in Combat Effect<\/span>. AI and drones enhance targeting.<\/span><\/p>\n Reduction in Collateral Damage<\/span>. UAVs fly missions with high risk, ultimately reducing civilian casualties.<\/span><\/p>\n Creating levels of logistics<\/span>. Predictive maintenance continues to reduce both operational downtime and costs.<\/span><\/p>\n Challenges & Ethical Issues<\/u><\/span><\/p>\n Autonomy versus Control<\/span>. Fully autonomous systems raise a question of who is responsible.<\/span><\/p>\n Cybersecurity and Operational Risk<\/span>. AI systems can be hacked and\/or manipulated.<\/span><\/p>\n Bias and Mistakes<\/span>. Incorrect target identification may result in unwanted collateral civilian casualties.<\/span><\/p>\n International Arms Race<\/span>. The Race for sophisticated AI weapons systems potentially destabilises international security.\u00a0<\/span><\/p>\n Prospects in the Future<\/u><\/span><\/p>\n Greater Autonomy<\/span>. UCAVs will function independently in high-risk operations.<\/span><\/p>\n Hypersonic Weapons<\/span>. AI will improve missile accuracy and velocity.<\/span><\/p>\n Quantum Integration<\/span>. Artificial intelligence and quantum computing will transform data processing used in predictive analytics and threat detection.<\/span><\/p>\n Counter-AI Warfare<\/span>. Armed forces will devise methods for nullifying adversary AI capabilities.<\/span><\/p>\n Ethical Regulation<\/span>. Strong guidelines must be put in place to deal with ethical and strategic issues.<\/span><\/p>\n <\/p>\n Security and Safety Risks to Aviation<\/u><\/strong><\/span><\/p>\n Security Risks<\/u><\/span><\/p>\n Data Poisoning and Adversarial Attacks: AI inputs can maliciously be manipulated and affect flight controls, navigation, or airport functionality.<\/span><\/p>\n System Vulnerabilities<\/span>. Ageing infrastructure can be susceptible to AI-based cyberattacks (e.g., ADS-B hijacking) and needs strong firewalls and intrusion detection.<\/span><\/p>\n Generative AI Threats<\/span>. AI might be used to create deceptive data or evade security.<\/span><\/p>\n Encryption Threats<\/span>. QC algorithms (e.g., Shor’s) might compromise public-key cryptography (RSA, ECC), endangering data breaches or spoofed signals in avionics and communications.<\/span><\/p>\n Harvest Now, Decrypt Later<\/span>. Threats may carry encrypted flight data for later decryption, compromising flight plans and military communications.<\/span><\/p>\n Complex Attack Surfaces<\/span>. Multiple layers of interconnected networks and avionics increase threats that are capable of quantum attacks.<\/span><\/p>\n Safety Risks<\/u><\/span><\/p>\n Algorithmic Errors<\/span>. AI bias or misinterpretation can lead to incorrect commands for autopilot or navigation decisions, resulting in accidents.<\/span><\/p>\n Over-Reliance<\/span>. AI reliance may negatively impact pilot proficiency; however, in-flight analysis can strengthen safety.<\/span><\/p>\n Transparency<\/span>. Black box AI channels pilot interpretation and overt truth.<\/span><\/p>\n Semi-Autonomous Systems<\/span>. The likelihood of a failure of autonomous operations in rare cases is significant.<\/span><\/p>\n Simulation Errors<\/span>. QC’s current error rates could lead to defective designs exposed via QC, and lead to unsafe airframes.<\/span><\/p>\n Cyber-Driven Safety Critical Hazards<\/span>. Quantum cyberattacks may disrupt avionics and navigation, leading to failures and unsafe operations.<\/span><\/p>\n