5.22 Promote and Implement Responsible Emerging Technology Practices
The organization has devised and implemented responsible policies related to artificial intelligence, the Internet of Things (IoT), Web3 (Decentralized Web, blockchain, etc), and related emerging technologies.
Criteria
- Emerging Technologies: The organization has public-facing policies in place for emerging technologies, and all such technologies are ethically sourced, screened, validated, and implemented in a non-discriminatory, responsible manner.
- Disruptive Technology: The organization shows how it up-skills workers as new technologies and practices potentially disrupt its business model.
- Technology Legislation: The organization supports and complies with responsible legislation related to automation and emerging technologies (such as the EU AI Act).
- Environmental Responsibilities: Organizations must consider, audit, and account for any environmental considerations that may derive from the use of emerging technologies they wish to either promote or implement within a chosen setting. Also note that this should include third-party choices, the “expense” (in terms of waste or emissions) of the utilization of the technology to create a desired result and consequential issues to the environment that may arise from its deployment.
- Quantum Resilience: Don’t roll out post-quantum encryption for high-traffic services that don’t need resilience against harvest now, decrypt later.
Impact
High
Effort
Medium
Benefits
- Operations:
Organizations that prioritize ongoing learning and continuous improvement build stronger teams that can adapt more quickly. - Economic:
Organizations with clear policies related to digital disruption are more resilient and can pivot more quickly than those without, and organizations with clear emerging technology policies are at less risk of any number of potential threats, including legal action.
GRI
- materials: High
- energy: High
- water: High
- emissions: High
Example
- How one business encourages innovation by setting aside 10% of time for learning.
Resources
- 3rd Global CryptoAsset Benchmarking Study (PDF)
- A sustainable internet: Missing pieces to a healthy future
- AI and crypto mining are driving up data centers’ energy use
- AI Environmental Equity
- AI Regulation Around The World
- AI’s Climate Impact Goes beyond Its Emissions
- Are harvest now, decrypt later cyberattacks actually happening?
- Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models
- Crypto and blockchain must accept they have a problem, then lead in sustainability
- Cryptocurrency’s Dirty Secret: Energy Consumption
- Digital aspects and the environment
- Digital education: The unique learning ecosystem TechUcation
- Dismantling the Quantum Threat
- Ecological Awareness for the Decentralized Web
- EU Artificial Intelligence Act
- Generating AI Images Uses as Much Energy as Charging Your Phone, Study Finds
- [GPFEDS] 1.7 – Strategy (Encryption) (PDF)
- [GPFEDS] 7.4 – Back-End (Consensus Mechanism) (PDF)
- [GPFEDS] 9.1-7 – Algorithms (Complete Chapter) (PDF)
- In battle against climate crisis, don’t overlook the blockchain
- Sustainability of Bitcoin and its Impact on the Environment
- Sustainable Ux in VR (PPT)
- The cyber-consciousness of environmental assessment
- The growing energy footprint of artificial intelligence
- The role of artificial intelligence in achieving the Sustainable Development Goals
- The Wholegrain guide to ethical use of AI
- United Nations [SDGS] Goal 1 (Poverty)
- United Nations [SDGS] Goal 10 (Inequality)
- United Nations [SDGS] Goal 16 (Sustainable Society)
- United Nations [SDGS] Goal 17 (Global Partnership)
- Web3 and Sustainability
- Web3 and sustainability: Benefits and risks
- What is the environmental impact of Web3?
- What Is the Future of Quantum-Proof Encryption?
- Why Blockchain, NFTs, And Web3 Have A Sustainability Problem
- Why We Need To Be UpSkilling The Current Workforce For The Green Economy