Over the course of 2022, 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.
The Future of Automation and The Recent Industrial Robot Sales Surge
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?
The 2022 OODA Loop Series: Autonomous Everything
Autonomous Everything: The First Autonomous Ship Crosses the Atlantic Ocean
Opportunities for Advantage: A Real-Time, Precise, Accurate, Interoperable OS for Autonomous Systems
Safety Performance Will Drive the Future of Self-Driving Cars
Autonomous Everything: The Workforce and The Future of Automated Port Terminals
OODA Network Member Junaid Islam on Security Automation and Automated Continuous Threat Testing
OODA Network Member Junaid Islam on Emerging AI-based Zero Trust for Smart Infrastructure
Mergeflow CEO and OODA Network Member Florian Wolf on “Small Data” (Part 1 of 2)
Mobile, Autonomous 3D-printed Drone Manufacturing: We now explore Orbital Composites’ work with United States Air Force to create mobile, autonomous 3D-printed drone manufacturing capabilities.
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