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Panel Description
From Amazon warehouses to military conflict in Ukraine we have become increasingly dependent on automated and autonomous platforms. This session will explore the current state of the field with a specific focus on the impact to national and economic security.
Matthew Steckman, CRO, Andruil Industries
Duyane Norman, DIU
Panelists Biographies
Matthew Steckman is Chief Revenue Officer for Anduril Industries. He is responsible for new business and customer success with a focus on U.S. and international governments as well as large companies facing infrastructure security challenges. Prior to Anduril, Matt served as Chief Revenue Officer for Zipline International, the world’s first drone delivery company focusing on medical and blood products. He divided his time between the U.S. and emerging markets and forged a first-of-its-kind partnership with the U.S. Government to provide Zipline’s lifesaving service to rural communities. Previously, Matt held several leadership positions at Palantir Technologies, running internal business operations and owning relationships with the company’s largest customers.
By or featuring Matthew Steckman:
Duyane Norman is an independent consultant and advisor amd, after retiring from CIA in March 2019 as a member of the CIA’s Senior Intelligence Service, he currently leads the Defense Innovation Unit’s engagement with the Department of Defense’s Agencies and Activities and serves as DIU’s link to the Intelligence Community. Duyane spent nearly 30 years in the CIA with three Chief of Station and multiple other tours in a variety of interesting geographies and also had a focus on technology issues serving as Deputy Director of the Office of Technical Service within CIA’s Directorate of Science and Technology, and as a member of the CIA Counterterrorism Center’s Incident Response Team. Duyane is a recognized IC leader in innovation, having founded and led the CIA’s Station of the Future Program and designed the transformational strategy adopted as the number one investment priority for the Directorate of Science and Technology for FY20-25. Duyane established a reputation as an innovator and a disruptor looking for ways for the intelligence services to flourish given the fast pace of technological change and the dynamic threats emerging on the global landscape.
By or featuring Duyane Norman:
The Future of Automation In All Its Forms: In a series of posts entitled Autonomous Everything, we explored automation in all its technological forms, including legacy working assumptions about the term itself. Autonomy is not just for the future of the car and personal mobility but includes powerful platforms in a broad autonomous future. We began the series in June at the bleeding edge of autonomous vehicles, with a description of the first autonomous ship to cross the Atlantic Ocean.
Automation, as a subject for OODA Loop research and analysis, cuts a broad swath across many industry verticals. Specific areas of interest emerged that we thought would be of interest to the OODA Loop membership:
Security Automation: Specifically, using automation for repetitive and time-consuming tasks for external cyber threats and internal information technology security. What are the safety and risk variables of this type of IT-based automation?
Automation and the Workforce: How is this implemented and what are the objectives: Efficiencies? Collaboration? Scalability? Cost-cutting? Innovation in operations? Does this type of automation always map back to a reduction in the workforce?
Automation – or Augmentation – of the workforce: The perennial debate surrounding robotics automation of the workforce is whether will jobs be 100% automated (with large-scale job elimination and job loss). Or will there always be a need for a human factor in certain industry verticals, translating into machine augmentation of certain tasks and operations, which a human operator integrated into the robotics design?
Autonomous Vehicles as Automation: This one is a bit tricky: but think of an autonomous fleet of trucking vehicles, for example, as one automated system in a larger production and distribution ecosystem or supply chain. Where is the innovation at this economy of scale? How do the business issues differ, if at all, at this scale of operations?
Automation of AI/Machine Learning Training Models: Can and should machine learning models retrain automatically? Should there be a human touchpoint integrated into this retraining process, to guard against biases becoming embedded into an AI system and/or the risk of AI Accidents when retraining is left unsupervised prematurely?
Automation Case Studies: Where are the best-in-class examples of automation, in the federal space and the private sector, worth researching and analyzing for strategic insights?
Industry Standardization: Like TCP/IP (or any of the IEEE ISO standards) what are the emergent industry standards which will allow for seamless interoperability and widespread commercial scalability? Are some commercial releases operating in a ‘closed garden” architecture? If so, is there a clear competitive advantage to such an approach?