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14.1 Artificial intelligence and big data in sustainability reporting

9 min read•july 30, 2024

and are revolutionizing . These technologies automate data collection, process massive datasets, and uncover hidden insights. They're making reporting faster, more accurate, and more predictive than ever before.

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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But with great power comes great responsibility. AI and big data in sustainability reporting raise ethical concerns about privacy, bias, and transparency. Companies must navigate these challenges carefully to harness the benefits while maintaining trust and accountability.

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Automating Sustainability Data Collection and Analysis

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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • AI and big data automate the collection, processing, and analysis of large volumes of sustainability data from various sources (sensors, satellite imagery, social media, corporate databases)
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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • algorithms identify patterns, trends, and correlations in sustainability data enabling more accurate and timely insights for decision-making and reporting
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Top images from around the web for AI and Big Data for Sustainability Reporting

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- For example, machine learning can detect anomalies in energy consumption data indicating potential inefficiencies or equipment failures
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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • techniques extract relevant sustainability information from unstructured data sources (news articles, reports, stakeholder feedback)
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Top images from around the web for AI and Big Data for Sustainability Reporting

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- NLP can identify key themes, sentiment, and entities related to sustainability topics from text data, such as customer reviews or employee surveys
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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • AI-powered forecast future sustainability performance, risks, and opportunities allowing organizations to proactively address potential issues and optimize their strategies
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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Predictive models can estimate the likelihood and impact of sustainability risks (supply chain disruptions, climate change effects) based on historical data and scenario analysis
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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Leveraging Big Data Technologies for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • Big data technologies (cloud computing, distributed processing) enable the storage, management, and analysis of massive sustainability datasets in real-time improving the efficiency and scalability of reporting processes
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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Cloud-based platforms (AWS, Azure) provide scalable and cost-effective infrastructure for storing and processing large sustainability datasets
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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Distributed processing frameworks (Hadoop, Spark) allow for parallel processing of sustainability data across multiple nodes, reducing analysis time and enabling real-time insights
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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • The integration of AI and big data into sustainability reporting may require new skills, roles, and collaborations within organizations (data scientists, AI engineers, sustainability experts) working together to design and implement effective solutions
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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Cross-functional teams with diverse expertise can ensure that AI and big data solutions align with sustainability goals, regulatory requirements, and stakeholder expectations
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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Upskilling and reskilling programs can help existing employees acquire the necessary knowledge and skills to work with AI and big data in sustainability reporting
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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Benefits and Challenges of AI in Sustainability Data Analysis

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Benefits of AI for Sustainability Data Analysis

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  • Increased accuracy and reliability of sustainability data through automated data collection and validation reducing human errors and biases
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- AI algorithms can validate sustainability data against predefined rules and thresholds flagging potential errors or inconsistencies for manual review
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- Automated data collection from IoT devices and sensors reduces the risk of manual data entry errors and ensures consistent [data quality](https://www.fiveableKeyTerm:Data_Quality)
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  • Enhanced efficiency and speed of data processing and analysis enabling faster and more frequent reporting cycles
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- AI algorithms can process large volumes of sustainability data in real-time providing up-to-date insights for decision-making and reporting
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- Automated data processing frees up human resources for more strategic and value-added activities (stakeholder engagement, innovation)
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  • Improved insights and decision-making through the identification of complex patterns, trends, and correlations in sustainability data
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- Machine learning algorithms can uncover non-linear relationships and hidden factors influencing sustainability performance (weather patterns, consumer behavior)
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- AI-powered data visualization and dashboards provide intuitive and actionable insights for sustainability managers and executives
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  • Reduced costs associated with manual data collection, processing, and reporting as AI and big data technologies can automate many tasks
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- Automated data collection and processing eliminate the need for manual data entry and manipulation reducing labor costs and time
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- Cloud-based AI and big data solutions offer scalable and cost-effective alternatives to on-premise infrastructure and software licenses
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Challenges of AI for Sustainability Data Analysis

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  • Data quality and availability issues as AI and big data rely on accurate, complete, and consistent data from various sources which may be difficult to obtain or integrate
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- Sustainability data may be siloed across different systems, formats, and organizational units requiring data cleaning, transformation, and integration efforts
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- External sustainability data (supplier information, customer feedback) may be incomplete, unstructured, or unreliable affecting the accuracy of AI-powered insights
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  • Lack of standardization and interoperability among different sustainability data sources and formats making it challenging to aggregate and analyze data effectively
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- Sustainability reporting frameworks and standards (GRI, SASB) may have different data requirements and definitions hindering data comparability and benchmarking
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- Legacy systems and proprietary data formats may not be compatible with modern AI and big data technologies requiring data migration and transformation efforts
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  • Skill gaps and resource constraints as organizations may lack the expertise, infrastructure, and budget to implement and maintain AI and big data solutions for sustainability reporting
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- Sustainability teams may not have the technical skills or experience to design, develop, and deploy AI and big data solutions requiring collaboration with IT and data science teams
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- Implementing and maintaining AI and big data infrastructure (hardware, software, cloud services) may require significant upfront and ongoing investments
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  • Ethical and privacy concerns as the collection, use, and sharing of sensitive sustainability data may raise issues related to data ownership, consent, and transparency
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- Collecting and analyzing employee or customer data for sustainability reporting may require informed consent and strict data protection measures to comply with privacy regulations (GDPR)
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- The use of AI algorithms for sustainability decision-making may raise concerns about bias, fairness, and accountability requiring transparent and [ethical AI governance](https://www.fiveableKeyTerm:ethical_ai_governance) frameworks
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AI Impact on Sustainability Reporting Practices

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Transforming Sustainability Reporting Processes

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  • AI and big data are likely to transform sustainability reporting from a periodic, retrospective exercise to a continuous, real-time process enabling more timely and actionable insights for stakeholders
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- Real-time data collection and analysis allow for on-demand sustainability reporting and alerts reducing the lag between performance and disclosure
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- Continuous monitoring and feedback loops enable proactive sustainability management and course correction based on real-time insights
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  • The adoption of AI and big data may drive the development of new , frameworks, and standards that leverage the capabilities of these technologies (dynamic materiality assessments, predictive risk management)
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- AI-powered materiality assessments can dynamically prioritize sustainability topics based on real-time stakeholder feedback and market trends
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- Predictive risk models can identify and quantify emerging sustainability risks (climate change, social unrest) informing strategic planning and risk disclosures
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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • AI and big data may enable more granular and context-specific sustainability reporting allowing organizations to tailor their disclosures to the needs and preferences of different stakeholder groups
Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Machine learning algorithms can segment stakeholders based on their sustainability interests and information needs enabling targeted and personalized reporting
Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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- NLP techniques can analyze stakeholder feedback and sentiment in real-time informing sustainability strategy and communication
Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Implications for Assurance and Verification

Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • The use of AI and big data in sustainability reporting may raise new challenges and opportunities for assurance and verification as traditional audit approaches may need to adapt to the complexity and opacity of these technologies
Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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- AI algorithms and big data processes may be difficult to audit and validate due to their complexity, scale, and constant evolution requiring new assurance skills and methodologies
Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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- The use of AI and big data may enable more automated and continuous assurance processes (real-time data validation, anomaly detection) complementing manual audits
Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • The integration of AI and big data into sustainability reporting may require new skills, roles, and collaborations within organizations (data scientists, AI engineers, sustainability experts) working together to design and implement effective solutions
Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Assurance providers may need to recruit or train professionals with AI and big data skills to effectively audit and validate sustainability reporting processes
Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Collaboration between sustainability, IT, and assurance teams may be necessary to design and implement robust and reliable AI and big data solutions for sustainability reporting
Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Ethical Considerations in AI-Powered Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Data Privacy and Security

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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • and security ensure that the collection, storage, and use of sustainability data comply with relevant laws, regulations, and best practices to protect individual and organizational privacy rights
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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Sustainability data may include sensitive personal information (employee health data, customer preferences) requiring strict data protection measures (encryption, access controls)
Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Organizations need to obtain informed consent from individuals before collecting and using their data for sustainability reporting purposes in compliance with privacy regulations (GDPR, CCPA)
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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • The use of AI and big data in sustainability reporting may require new skills, roles, and collaborations within organizations (data scientists, AI engineers, sustainability experts) working together to design and implement effective solutions
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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Cross-functional teams with expertise in data privacy and security can ensure that AI and big data solutions for sustainability reporting adhere to legal and ethical standards
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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Regular privacy impact assessments and security audits can identify and mitigate potential risks and vulnerabilities in AI and big data systems used for sustainability reporting
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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Top images from around the web for AI and Big Data for Sustainability Reporting

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Algorithmic Bias and Fairness

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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • and fairness address the potential for AI algorithms to perpetuate or amplify biases based on factors (race, gender, socioeconomic status) which may lead to discriminatory or unfair sustainability assessments and decisions
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Top images from around the web for AI and Big Data for Sustainability Reporting

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- AI algorithms trained on historical sustainability data may inherit and reinforce past biases and inequalities (gender pay gap, racial discrimination) affecting the accuracy and fairness of sustainability insights
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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Biased AI algorithms may lead to skewed sustainability ratings, rankings, and investment decisions disadvantaging certain groups or organizations
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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • provide clear and understandable information about how AI and big data are being used in sustainability reporting including the data sources, algorithms, and assumptions involved to enable stakeholder scrutiny and accountability
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- Organizations should disclose the methodologies, limitations, and potential biases of their AI and big data approaches to sustainability reporting allowing stakeholders to interpret and contextualize the results
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- Explainable AI techniques (model interpretation, feature importance) can help stakeholders understand how AI algorithms arrive at sustainability insights and decisions fostering trust and accountability
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Top images from around the web for AI and Big Data for Sustainability Reporting

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  • Responsibility and accountability establish clear roles, responsibilities, and mechanisms for governing the use of AI and big data in sustainability reporting including oversight, auditing, and redress procedures in case of errors, misuse, or harm
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Top images from around the web for AI and Big Data for Sustainability Reporting

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- Organizations should designate accountable individuals or committees to oversee the ethical and responsible use of AI and big data in sustainability reporting setting policies and guidelines
Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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- Regular audits and impact assessments can monitor the performance and compliance of AI and big data systems used for sustainability reporting identifying and correcting any issues or harms
Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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Stakeholder Engagement and Consent

Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • involve relevant stakeholders (employees, customers, communities) in the design, implementation, and evaluation of AI and big data solutions for sustainability reporting and obtaining their informed consent where appropriate
Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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1 of 3

Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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- Organizations should consult with diverse stakeholders to understand their expectations, concerns, and priorities regarding the use of AI and big data in sustainability reporting incorporating their feedback into solution design and governance
Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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- Informed consent processes should clearly communicate the purposes, benefits, risks, and choices associated with the collection and use of personal data for sustainability reporting allowing individuals to make voluntary and informed decisions
Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • The use of AI and big data in sustainability reporting may raise new challenges and opportunities for assurance and verification as traditional audit approaches may need to adapt to the complexity and opacity of these technologies
Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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- Assurance providers may need to engage with stakeholders to understand their expectations and concerns regarding the ethical and responsible use of AI and big data in sustainability reporting incorporating their perspectives into assurance criteria and procedures
Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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Top images from around the web for AI and Big Data for Sustainability Reporting

  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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  • Sustainability Metrics and Rating Systems | Sustainability: A Comprehensive Foundation View original

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  • Frontiers | The Applicability of Big Data in Climate Change Research: The Importance of System ... View original

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- Stakeholder engagement can help identify and prioritize the ethical risks and impacts of AI and big data in sustainability reporting informing the scope and focus of assurance activities
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About FiveableBlogCareersTestimonialsCode of ConductTerms of UsePrivacy PolicyCCPA Privacy Policy
Resources
Cram ModeAP Score CalculatorsStudy GuidesPractice QuizzesGlossaryCrisis Text LineRequest a Feature
© 2024 Fiveable Inc. All rights reserved.
AP® and SAT® are trademarks registered by the College Board, which is not affiliated with, and does not endorse this website.
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