Explore our AIS Communities
We welcome any and all volunteers to join our work. View the groups below to learn more about each program and how to join.
IC20-008 - The IEEE Trusted Data & Artificial Intelligence Systems (AIS) Playbook for Finance Initiative
The purpose of the Financial Service Playbook is to curate, summarize and contextualize Trusted Data & AI best practices for the financial sector around design principles, standards and certifications. The 1st edition of the Playbook will focus on Personalized Marketing Offers, Loan and Deposit Pricing, Credit Adjudication, Customer Sentiment Tracking, Customer Lifetime Value, Customer Segmentation, Securities – High Frequency Trading, Robo-Advisors, etc. IEEE’s Ethically Aligned Design, P7000 Standards and ECPAIS certifications will be incorporated to align with anticipated European / Singapore / Canadian monetary regulatory authorities and policy frameworks.
Goals for this IC Activity include the creation of set of implementations guidelines framed as a “Playbook” along with virtual trainings, in-person workshops and potential PARs to drive adoption and continuous enhancement for the Playbook.
IC20-007 - The IEEE Global Artificial Intelligence Systems Well-being Initiative
The goal of this Industry Connections group is to continue and proliferate the existing work of The IEEE Standards Association focused on well-being and technology, which includes an event at the European Parliament in 2017, the well-being chapter of Ethically Aligned Design, and IEEE Std 7010-2020, Recommended Practice for Assessing the Impact of Autonomous and Intelligent Systems on Human Well-Being which was published on May 1st, 2020.
Directly mirroring and supporting IEEE’s tagline of “Advancing Technology for Humanity,” this well-being Initiative will continue the pioneering work of IEEE to provably align the increase of human well-being and ecological sustainability by providing “AIS Creators” (corporations, engineers, data scientists, academics, marketers, policy makers) and end users the resources, knowledge and tools needed to support a shift whereby AIS Creators are able and willing to help safeguard and improve human well-being and ecological sustainability through their AIS creations today and into the future.
IC20-006 - The IEEE Applied AIS Risk and Impact Framework Initiative
In accordance with the evolving regulation around Artificial Intelligence Systems (AIS), this group would understand and propose an applied risk framework or assessment. In order to achieve these goals, the group would understand existing risk approaches in the fields of finance, cybersecurity, and more, identify gaps introduced by AI, and determine an approach to create a fit-to-purpose applied assessment for AI to determine riskiness and identify approaches to mitigate risk.
Goals for this IC include the creation of a general platform for AIS risk assessment reports, white papers, the development of multiple PARs and general coordination activities with leading global policy makers and organizations.
IC20-004 - Assessment of Standardization Gaps for Safe Automated Driving
Safety comes first for automated driving. Policy makers expect that AVs will significantly reduce the number of road fatalities (‘zero-accident’ vision). New technologies impose new challenges on safety engineering:
- Inductive reasoning
- Blackbox functionality
- Governance of algorithmic decision making
- Novel ICT oriented vehicle architectures
- Redundancies and tradeoffs between enabling technologies
- Verification and validation of automation levels
Existing standards need to be evolved and new standards are needed to ensure safety despite increasing automated driving complexity.
IC20-003 - AI-driven Innovation for Cities and People
The primary goal of this Activity is to provide cities a mechanism to support responsible Artificial Intelligence (AI) Systems innovation through proper governance mechanisms to support diverse access to problem solving with AI.
IC20-001 - Pre-Standardization Activities on Industrial AI
Industrial AI differs from consumer AI applications in terms of data quality and privacy aspects; information content, and impact of AI on various stakeholders. In order to clearly identify requirement towards standardization, a use case driven approach needs to be developed to clearly establish expectations from all stakeholders. Since there are already established standards governing industrial automation, it is important to identify possible overlaps with Industrial AI requirements and identify potential gaps that need to be bridged by new standards. A focused industrial AI based approach will help in accelerating this work.
IC19-007 - Pre-Standardization Studies for Indian Language Resources
Identification of use cases that could lead to proposals for standards to govern Language Resources for Indian languages is the motivation of this effort. Language Resources include Speech, Language data and descriptions which are made available in a machine readable form and used for developing, evaluating and improving algorithms in the area of natural language and Speech processing. Such standards can also be used for language studies, localization of software, electronic publishing and any purpose for researchers, subject area specialists etc.
IC19-006 - Data Trading System Initiative
In the context of increasing data generation through IoT and the ability to augment data through algorithmic decision making, this IC activity proposes that the sharing of data should shift from a centralized system to an autonomous distributed sharing model, called the data trading environment. In this environment, it is assumed that multiple different entities supply and receive data equitably from each other, and there has to be a compensation flow between the supplier and receiver. Multiple entities can trade data directly or through a mediator in this data trading environment. This IC Activity aims to propose new standards projects to enable this environment.
IC19-005 - Public Knowledge Graphs
This activity seeks to identify and support the creation of open, federated graphs of knowledge, using available protocols for storage and mirroring, alignment of different graphs, clustering and disambiguation, annotation, tracing and adding provenance. Separating the storage of knowledge + its known provenance + its implications about the world, from its inferred provenance and implications, and the evaluations of its truth or reliability by others. The focus will be on public knowledge and public interfaces, and on machine-mediated access and knowledge representations, for constructing world and local models for machine learning.
IC19-003 - MyData Health
MyData Health seeks to create a participatory design process for creation of whitepapers on the topic of creating a fair health data economy. MyData Health seeks to “level the playing field” for all stakeholders in this important conversation on how to create a “fair” health data economy to serve the potential benefits for each individual patient, global public health, and society at large.
IC18-005 - African Standardization Strategy and Roadmap for the 4th Industrial Revolution
The Africa Standardization Strategy and Roadmap for the 4th Industrial Revolution will provide a prioritization and very specific implementation plan focusing on standardization aspects and related training needs to help deliver the broader objectives set out by the Agenda 2063. It brings together institutions to engage and provide inputs into a shared vision that enables deployment of future platforms in a more seamless manner.
This strategy and roadmap will benefit the African standardization and technology communities, as well as related policy communities. These documents aim to enable the community to address the needs and challenges in a more coordinated and efficient manner. This is critical in the context of the trends of regional integration, such as through the African Continental Free Trade Agreement (AfCFTA) and Digital Single Market.
IC18-004 - Ethics Certification Program for Autonomous and Intelligent Systems (ECPAIS)
The goal of The IEEE Ethically Aligned Certification Program Initiative for Autonomous and Intelligent Systems (ECPAIS) is to provide the world’s first (based on our research) specification and body of its kind to enable a badge or mark for A/IS products, services and systems. Specifically, ECPAIS will enable these badges or marks based on the processes organizations seeking certification have undertaken to earn them.
IC17-006 - Big Data Governance and Metadata Management
The proposed work will guide how big data and big data exchange is governed. It will enable consumers of big data to better understand what is available and how to access it. It will help producers of big data properly set expectations and take steps to ensure that their datasets can be maintained and shared in accordance with their wishes. It will help organizations that store big data make decisions concerning how the big data is stored, curated, exposed, and otherwise governed so as to best serve consumers and producers.
IC17-002 - Digital Inclusion, Identity, Trust, and Agency
This Industry Connections Activity will identify and create consensus throughout technologies that have a potential to alter policy and business landscape, with particular focus on disruptive innovation. It will address inclusion through trust and agency, working toward solutions that promote agency over our data, cyber-identity and internet-related security including, but not limited to, distributed ledger technologies.
IC16-002 - The Global Initiative on Ethics of Autonomous and Intelligent Systems
Bringing together experts in fields relating to autonomous systems (e.g., Robotics, Artificial Intelligence, Computational Intelligence, Machine Learning, Deep Learning, Cognitive Computing, Affective Computing) to identify and address the ethical considerations related to the design of autonomous systems and the issues they involve.
IC16-001 - Open Data
Bringing together experts in fields relating to autonomous systems (e.g., Robotics, Artificial Intelligence, Computational Intelligence, Machine Learning, Deep Learning, Cognitive Computing, Affective Computing) to identify and address the ethical considerations related to the design of autonomous systems and the issues they involve.