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Responsible Augmented Intelligence For Those Who Make The Worldtm Augmenting Intelligence In A Diversified Industrial
Mark T. Maybury, Chief Technology Officer, Stanley Black & Decker


Mark T. Maybury, Chief Technology Officer, Stanley Black & Decker
As Figure 1 illustrates, our broad set of AI activities are accelerated by a center of excellence in AI and Data Analytics (AIDA), and a Chief AI Officer (CAIO) who champions AI across our businesses and functions. AI plays a key role in augmenting human intelligence by automating routine tasks. For example, we employ over 150 intelligent process automations delivering over $50M in value. In our global tool business, in addition to smart hand and power tools, intelligent building information modeling (BIM) systems can be enhanced by automated natural language processing and document, understanding to provide increased awareness, coordination and productivity for various construction stakeholders. In our industrial business, we deploy intelligent IoT for attachment predictive maintenance via InSite. In health and security, systems such as our Foresite vision-based gate analysis system, can anticipate and warn patients 30-40 days prior to a fall to prevent them and simultaneously preserve their privacy. And Pria, a conversational home health companion, can track medication dispensing and monitor health for caregivers. Finally, our supply chains and manufacturing processes are increasingly augmented by machine learning.
Figure 1. AI Accelerating A Global Diversified Industrial
Intelligent Manufacturing
Since 2014, our innovation journey has quickly accelerated, empowered by the fourth industrial manufacturing revolution which emphasizes transformation to intelligent cyber physical systems (de Boer et al. 2018). These systems enable a symbiotic relationship between human and machine intelligence resulting in manufacturing excellence. Organizations that fail to adopt, adapt or augment this intelligent manufacturing trend and compete effectively on the rate of learning and creativity, risk extinction (Kimura et al. 2019).
Our Industry 4.0 investment and strategy strives for socially responsible enterprise excellence, focusing on the most important value streams. We leverage a digital thread enabling Stanley Black & Decker to increase the speed and quality of manufacturing, accelerate our agility to refine or redesign products in manufacturing, and grow profitability through operations excellence and upskilling. Our intelligent manufacturing automation strategy is founded on a connected factory and enterprise that enables data collection for situation awareness, anticipatory analytics, distributed collaboration, and remote command and control. As summarized in Figure 2, our advanced manufacturing strategy incorporates IoT connected machines which provide an ability to sense infrastructure, machine, and human activity, enabling modeling and digital twins to be leveraged for an operational and financial advantage.
Figure 2. AI Empowered Manufactory enabling Industry 4.0 Transformation
Responsible AI For Those Who Make The WorldTM
Our deployment of AI and products and manufacturing is driven by our purpose of supporting the makers of the world, focused on building, creating and securing a better world for our customers, employees and communities. Artificial Intelligence (AI), which includes Machine Learning, promises to help us elevate that mission to make our lives more productive, safer, and more joyful. Appreciating that new technologies and methods can pose new risks to society, we have developed the following principles to guide the development of safe AI systems (IEEE 2021) at Stanley Black & Decker in alignment with our purpose as illustrated in Figure 3.
Figure 3. Responsible Artificial Intelligence
Be truthful and transparent
We will apply standards and protocols to create clarity and ensure understandable explanations (Maybury 2004) of the basis and reasoning underlying an AI system’s decisions and behaviors, and ensure user awareness of conditions that could lead to adverse outcomes (e.g., a biased decision, a risky action).
Ensure privacy and security
We will design solutions that use methods such as data and information minimization, aggregation, and de-identification to reduce privacy attack vectors. We will apply digital product security practices that ensure confidentiality, availability, and integrity.
Artificial Intelligence (AI), which includes Machine Learning, promises to help us elevate that mission to make our lives more productive, safer and more joyful
Ensure equity and mitigate bias via inclusivity
When designing solutions, we will ensure sufficient diversity and inclusion in their data, learning and testing to avoid biased training data, models, decisions, and outcomes. Diversified teams (e.g., SMEs, end users, security/safety experts) are needed to avoid unbalanced focus on system performance and optimization at the expense of system reliability, fairness, and/or safety. We aim for AI development and deployment teams that are inclusive across multiple kinds of diversity.
Create symbiotic human machine interactions
We aim to design solutions that effectively distribute tasks and workloads across humans and machines, ensuring appropriate roles and responsibilities (e.g., oversight over key decisions by humans, delegation of dull, dirty or dangerous tasks to machines). We seek to design effective human machine interfaces (Maybury and Wahlster 1998) including affordances that enable graceful degradation.
Be aware (of self and others) and beneficent
We will strive to ensure that AI solutions enforce appropriate self-limitations and design machine intensions and actions that are task and situation appropriate.
Be resilient
We will design solutions that are resilient by using methods such as diversified training and test sets that avoid classification failures, utilization of V&V methods and stress testing appropriate to the application and when switching environments. After systems are fielded, we will strive to actively monitor their performance in various deployment contexts and continuously assess their performance with (reinforcement) learning over time.
Summary
Stanley Black & Decker is leveraging Artificial Intelligence and Machine Learning to enhance products, accelerate manufacturing agility, and grow profitability. We are committed to equity, inclusion, safety, and sustainability. Given the criticality of AI and ML in work, home, and play, we aim to ensure our values are reflected in the realization of responsible products and services. Enabling responsible AI enables us to better serve humanity and be a force for global good for those who make the world.
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