2023¶

October 17, 2023
in Defense Technology, Digital Engineering, Organizational Learning
3 min read

Sim-to-real is an organizational-learning problem

The Defense Advanced Research Projects Agency (DARPA) is seeking proposals for Transfer from Imprecise and Abstract Models to Autonomous Technologies (TIAMAT). The program challenges a common assumption: instead of building ever more detailed simulations, diverse lower-fidelity environments may help autonomous systems learn concepts that transfer more readily to unfamiliar real-world settings.

The technical hypothesis is provocative. The management lesson is familiar: a model becomes dangerous when an organization forgets which parts of reality it left out.

October 15, 2023
in Human-Centered AI, Decision Support, Knowledge Strategy
3 min read

Expert judgment belongs in the system design

A new study from International Business Machines (IBM) researchers examines how machine-learning predictions might be adjusted when a domain expert's judgment conflicts with the model, particularly when a case is poorly represented in the training data. The work addresses a practical reality: experts and models often disagree for reasons that neither an accuracy score nor an appeal to experience can settle alone.

The disagreement should be treated as information.

October 5, 2023
in AI Strategy, Platform Engineering, Operating Models
3 min read

Inference is where AI strategy meets the budget

International Business Machines (IBM) Research has published a timely explanation of artificial intelligence inference—the moment when a trained model receives live input and produces a result. Training attracts attention because it creates the model. Inference is where the model becomes a recurring service, and where much of its lifetime cost and user experience accumulate.

For enterprise leaders, inference is not only an infrastructure concern. It is where an artificial intelligence (AI) portfolio meets a budget.

September 25, 2023
in Defense Technology, AI Assurance, Systems Engineering
3 min read

Trustworthy autonomy needs more than a better neural network

The Defense Advanced Research Projects Agency (DARPA) has selected teams for its Assured Neuro Symbolic Learning and Reasoning (ANSR) program. The program will explore architectures that combine data-driven neural learning with symbolic representations and reasoning, with the aim of improving robustness and assurance for autonomous systems.

The research matters because high performance and trustworthy behavior are not the same achievement.

September 19, 2023
in AI Governance, AI Security, Risk Management
3 min read

Scaling policies turn capability into a management trigger

Anthropic has published a Responsible Scaling Policy (RSP) that ties increasingly strong safety and security measures to evidence that a model has reached particular dangerous capabilities. The policy introduces Artificial Intelligence Safety Levels (ASLs), loosely inspired by the graduated containment used for biological hazards.

The specific thresholds will require continued research. The management pattern is already useful: decide in advance which evidence changes the organization's obligations.

September 12, 2023
in Defense Technology, Human-Centered AI, Systems Engineering
3 min read

Disconnected autonomy requires better mission boundaries

The Defense Advanced Research Projects Agency (DARPA) is seeking technology for its Rapid Experimental Missionized Autonomy (REMA) program. The objective is to add adaptable autonomy to commercial drones so they can continue a predefined mission when communication with the operator is lost.

Loss of connection is often described as a communications problem. For an autonomous system, it is also an authority problem: what may the machine continue to do when the person can no longer supervise it?

September 6, 2023
in AI Assurance, Human-Centered AI, Risk Management
3 min read

Multimodal AI requires multilayer evaluation

Microsoft Research has published an overview of responsible artificial intelligence work on multimodal systems—models that analyze or generate across text, images, audio, and other forms of data. The research highlights a practical problem: risks can appear in the combination even when each input looks acceptable on its own.

Evaluation must follow the system across modalities, interactions, and real-world effects.

August 28, 2023
in Defense Technology, Innovation Management, Operating Models
3 min read

Replicator is an organizational test of speed and scale

The Department of Defense (DoD) has announced the Replicator initiative, an effort to field attritable autonomous systems in multiple domains at a scale of thousands within 18 to 24 months. The goal is intentionally aggressive. It is meant not only to deliver systems, but to demonstrate a repeatable way to move relevant technology into warfighters' hands faster.

Replicator will be discussed as an autonomy and manufacturing challenge. It is equally an organizational-design challenge.