Key Themes from IATA WSOC 2023 - Data Alignment and Synergies across Operations & Safety

Key Themes from IATA WSOC 2023 with Data Alignment, Operations and Safety Synergies, AI Adoption and a Digital First Aviation Landscape High on the Agenda.

Data alignment and smarter collaboration across aviation operations and safety

As the inaugural event bringing together both aviation operations and safety, one of the overarching themes at the IATA WSOC conference in Hanoi was the increasing priority for alignment between aviation operations and safety in particular with regards to data, to foster even greater collaboration and join up previously unjoined dots. Breaking down data silos for data alignment and smarter collaboration across aviation operations and safety sectors is indispensable in the modern aviation landscape. For example, a recurring theme was the tighter integration of SMS data (e.g. ASAP report, textually rich, subjective) with Flight Data (FDM/FOQA) as an interesting area of data fusion that provides a system-wide view of risk.

The symbiotic relationship between aviation operations and safety and  thinking towards systems alignment across the two is seen as a strategic move creating a mutually reinforcing dynamic. Enhanced data analytics, predictive maintenance, and real-time monitoring not only optimize operational efficiency but also provide invaluable insights into potential safety hazards. Safety protocols, on the other hand, feed back into operations, influencing decisions related to flight routes, aircraft design, and crew training. A closer interaction and data alignment will foster a culture of continuous improvement. This alignment allows for real-time sharing and analysis of critical information, leading to more informed decision-making processes. Smarter collaboration involves the strategic use of this shared data, enabling stakeholders to anticipate challenges, optimize routes, and enhance safety protocols collaboratively.

 

Digitisation Acceleration - Digital innovation remains core to the future of aviation

The aviation industry has a long history of change and evolution. Change is a certainty in aviation and digital transformation is key to this change. Digital transformation is not just about technology and processes, it’s also a required mindset and culture, and regulators need to be brought on the digital transformation journey. Embracing a digital-first and data-driven approach will continue to transform aviation operations and safety into an interconnected system.

  

Digital to attract, empower and retain the next gen aviation workforce

The aviation workforce gap as a result of the 2020 / 2021 pandemic continues to have an impact on the safety and operations workforce. Less experienced ground crew, pilots with fewer flying hours, less people to do more. Additionally, employees are no longer ‘static’ in aviation careers. Aviation safety and operations careers are no longer life long as they used to be. The new generation aviation workforce is fluid and won’t stay if they are not empowered with the right digital tools and modern systems. As an industry, airlines need to consider ‘Are we recruiting the right people?’,  ‘Do they have right tools to do their job effectively?’ and ‘Are we catering for a digital first workforce to attract the next generation aviation employee?

AI – No over regulation and no over standardisation  

The aviation industry has a history and culture of being ‘in control’ –and to always understand what it is doing. AI adoption requires a departure from this decades old way of doing things and thinking. In order to embrace AI, a culture, mindset and acceptance shift is needed. In the words of Mark Searle, Global Director of Safety at IATA, the aviation industry needs to “Get comfortable with using AI but not over regulate or over standardise in the process”. To allow AI to support human decision to making, making decisions that are more efficient, more often. Balancing the deployment of AI in aviation with a stance of no over regulation and no over standardisation is important to harness the potential of AI. Over regulation could stifle the implementation of AI, Over standardisation would limit the flexibility needed for airlines to adapt AI systems to their specific needs. A nuanced approach that promotes responsible AI development, while leaving room for customisation and adaptation, ensures that the aviation sector can embrace the benefits of AI while mitigating potential risks.

Explainable AI to enhance AI-human collaboration, to foster trust and bridge the gap between AI and human understanding  

An interesting take away from the closing keynote Futurist Matthew Griffin of the 311 Institute and XPotential University relates to ‘Explainable AI’,  a critical field within artificial intelligence that focuses on developing algorithms and methods that can be easily understood and interpreted by humans. In the complex landscape of advanced machine learning models, where intricate neural networks and algorithms make decisions, understanding the reasoning behind these decisions is vital. Explainable AI aims to demystify these black-box models, providing insights into how they reach specific AI-Based conclusions or predictions. By providing clear insights into the rationale behind AI-generated suggestions, enhancing human-AI collaboration, this allows aviation professionals to make clearly-informed decisions swiftly. This transparency not only fosters trust between AI systems and users but also enables aviation professionals to identify biases, errors, or vulnerabilities within the algorithms. Ultimately, Explainable AI plays a pivotal role in aviation ensuring that AI technologies are not only powerful but also accountable and interpretable, thereby bridging the gap between advanced AI capabilities and human comprehension.

Risk Based IOSA Adoption

Risk Based IOSA Adoption to identify and mitigate risks tailored to individual airlines  is enhancing overall safety measures, operational efficiency and improved regulatory compliance. The Risk Based IOSA route is proving to be a success and is being embraced by airlines with greater collaboration with regulators to improve safety outcomes. Risk is not the same in different parts of the world and Risk Based IOSA gives airlines a better insight into what happened and a more detailed type of audit while the auditor is more clear on what they are focusing on. Unlike traditional audits, Risk-Based IOSA focuses on identifying and mitigating specific risks tailored to individual airlines, allowing them to allocate resources effectively. By analyzing potential vulnerabilities in areas such as safety management systems, flight operations, and maintenance procedures, airlines can proactively address issues before they escalate, ensuring a higher level of safety for passengers and crew members.  

Future of SMS – An ongoing evolution of present-day SMS towards In-Time aviation SMS ...

…will be achieved through focusing on four key areas

1. Human-Centric SMS Systems  
   In dealing with increased density of air traffic and reduced margins for error, the key is ensuring the effective delivery of the right information to aviation crews visually or aurally – too much data can overwhelm crews or desensitise them to warnings. Hence, the design of  SMS and associated data delivery systems is just as important as unlocking insight in the best and most time efficient way.  
   
   
2. Digitally transformed infrastructure
   Digital remains high on the agenda and the industry needs to recognise that ongoing digital change, although not simple, is essential. This brings airlines on the journey from Reactive to Proactive and ultimately Predictive. Currently maturity along this journey varies within an airline, by airline, by region and by sector. Central a digitally transformed infrastructure is the a more collaborative  environment with increased data sharing and combination of data sets and leverage if AI.  
   
   
3. Data analysis and AI in Risk Management
   To become predictive, the aviation industry needs to prioritise operational risks to focus within datasets and manage risk at scale. For example, using data analysis to quickly identify unknown risks so they can be included within prioritisation considerations. Use insight from data analysis to inform improved system design which flows through to safety policy, safety policy as well as related tech platforms (hardware and software).  
   
   
4. Increased levels of automation and data sets
   In order to enable effective risk management within an increasingly complex and dense airspace, there is an increasing need for system-generated data (for example in helping to and mitigate self-separated traffic risk) and need for analysis of an increased combination of data sets. 

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