IT in general

The standard defines specific methodologies to help users certify how they approach accessing, collecting, storing, utilizing, sharing, and destroying child and student data. The standard provides specific metrics and conformance criteria regarding these types of uses from trusted global partners and how vendors and educational institutions can meet them.
You can look here for a preview of the Standard Document

Development Status: Under development
 

This standard describes specific methodologies to help users certify how they worked to address and eliminate issues of negative bias in the creation of their algorithms, where "negative bias" infers the usage of overly subjective or uniformed data sets or information known to be inconsistent with legislation concerning certain protected characteristics (such as race, gender, sexuality, etc.); or with instances of bias against groups not necessarily protected explicitly by legislation, but otherwise diminishing stakeholder or user well-being and for which there are good reasons to be considered inappropriate. Possible elements include (but are not limited to): benchmarking procedures and criteria for the selection of validation data sets for bias quality control; guidelines on establishing and communicating the application boundaries for which the algorithm has been designed and validated to guard against unintended consequences arising from out-of-bound application of algorithms; suggestions for user expectation management to mitigate bias due to incorrect interpretation of systems outputs by users (e.g. correlation vs. causation)
You can look here for a preview of the Standard Document

Development Status: Under development
 

This standard defines requirements for a systems/software engineering process for privacy-oriented considerations regarding products, services, and systems utilizing employee, customer or other external user's personal data. It extends across the life cycle from policy through development, quality assurance, and value realization. It includes a use case and data model (including metadata). It applies to organizations and projects that are developing and deploying products, systems, processes, and applications that involve personal information. By providing specific procedures, diagrams, and checklists, users of this standard will be able to perform a conformity assessment on their specific privacy practices. Privacy impact assessments (PIAs) are described as a tool for both identifying where privacy controls and measures are needed and for confirming they are in place.
You can look here for a preview of the Standard Document

Development Status: Under development

This standard describes measurable, testable levels of transparency, so that autonomous systems can be objectively assessed and levels of compliance determined.

Development Status: Under development

Working groups are open for experts and their contributions but experts need to either become IEEE-SA Members by paying an annual member fee or pay a per-ballot fee in order to participate in ballots.

Published standards can be purchased from IEEE.

You can look here for a preview of the Standard Document

The purpose of this standard is to have one overall methodological approach that specifies practices to manage privacy issues within the systems/software engineering life cycle processes.

This standard specifies the dimensions for the width, thickness, and curvature of 2-in video magnetic recording tape.

This standard specifies the frequency response and operating level for recorders and reproducers for audio 1 record for 2-in quadruplex video magnetic tape recording at 15 in/s and 7.5 in/s (381 mm/s and 190.5 mm/s), as defined in ANSI/SMPTE 6. It also specifies the field method of calibration of recorders and reproducers, utilizing the test tapes as defined in ANSI/SMPTE 8 and ANSI/SMPTE 11.

This family of engineering documents defines an extensible system of RTP-based essence streams referenced to a common reference clock, in a manner which specifies their timing relationships. — This standard specifies the system timing model and the requirements common to of all of the essence streams.

Master-Slave/Token-Passing (MS/TP) is a medium access control method for the RS-485 physical layer and is used primarily in building automation networks. This specification defines the frame format for transmission of IPv6 packets and the method of forming link-local and statelessly autoconfigured IPv6 addresses on MS/TP networks.

This International Standard is aimed at organizations that provide services to communities in cities, and manage the resulting data, as well as decision-makers and policy developers in cities
This International Standard describes, and gives guidance on, a smart city concept model (SCCM) that can provide the basis of interoperability between component systems of a smart city, by aligning the ontologies in use across different sectors. It includes:

• concepts (e.g. ORGANIZATION, PLACE, COMMUNITY, ITEM, METRIC, SERVICE, RESOURCE).

• relationships between concepts (e.g. ORGANIZATION has RESOURCEs, EVENT at a PLACE).

Source: https://www.iso.org/standard/53302.html

With the advent and rise of AI there is a risk that machine-to-machine decisions will be made with black-box inputs determined without input transparency to humans. In order to enable ethics-based AI, individuals will require the means to influence and determine the values, rules and inputs that guide the development of personalized algorithms and Artificial Intelligence. They will need an agent that can negotiate their individual rights and agency in a system of shared social norms, ethics and human rights that also foresee and helps the individual mitigate ethical implications of data processing. This approach will enable individuals to safely organize and share their personal information at a machine-readable level and enable a personalized AI to act as a proxy for machine-to-machine decisions. A key goal for the creation of this standard is to educate government and commercial actors why it is in their best interests to create the mechanisms for individuals to train Personal AI Agents to move beyond asymmetry and harmonize personal data usage for the future.

Standard: P7006 - Standard for Personal Data Artificial Intelligence (AI) Agent

Description: This standard describes the technical elements required to create and grant access to a personalized Artificial Intelligence (AI) that will comprise inputs, learning, ethics, rules and values controlled by individuals.

Development Status: Under development

This standard is designed to provide organizations with a set of clear guidelines and certifications guaranteeing they are storing, protecting, and utilizing employee data in an ethical and transparent way. It is also designed to help employers with an understanding that most individuals may not be tech-savvy enough to understand underlying issues of data usage, but still must be properly informed about the safety of their employee data to be provided with tools and services that provide proper opportunities for content based, pre-informed choice regarding how they share their information in the workplace. Modelled after the EU GDPR legislation, this Standard will be designed to be a form of "GDPR for Employees" guaranteeing that workers facing widespread automation issues potentially displacing their jobs will have control and influence over the personal information that directly represents a core asset of their identity and lives whether derived from work-flow monitoring or personal data storage.

Development Statuts: Under development

Openess: Working groups are open for experts and their contributions but experts need to either become IEEE-SA Members by paying an annual member fee or pay a per-ballot fee in order to participate in ballots.

Published standards can be purchased from IEEE.