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2024 ITU Kaleidoscope Academic Conference




           Inference: Technological interventions and process reforms  incidents reported in AIID predominantly relate to AI systems
           are required to widen the base of incident reporting.  developed by American companies, as evident from Table 7.
                                                              Further, the top sources of the reports submitted to AIID are
           Recommendation 5:   Develop standards for automated  from American or European newspapers, as detailed in Table
           incident reporting: Develop standards to enable automated  5.
           AI-incident reporting through the AI applications to
           supplement manual reporting.                       Inference:  Existing AI-incident databases particularly
                                                              lack representation from developing and underdeveloped
           5.6  Inadequate data-sharing protocols             countries.  Capturing AI incidents prevalent in these
                                                              underrepresented regions is crucial for developing mitigation
           Observation: As indicated in Table 9, the two databases  strategies. It is also essential in advancing the UN SDGs.
           allow downloading data in different formats, and both do
           not provide APIs for accessing data.  Further, there is  Recommendation 8:  ITU-led inclusive AI incident
           inconsistency related to the information accessible from the  reporting: Encourage international collaboration facilitated
           two databases (Table 9). The submitter names are accessible  by UN organizations, such as ITU, to establish standardized
           in AIID but not in AIAAIC. Similarly, AIID provides access  protocols for AI-incident reporting, prioritizing inclusivity
           to the details of the harmed parties, but in AIAAIC, harm  from developing countries. This promotes comprehensive
           data is only accessible to Premium Members.        understanding and mitigation aligned with UN SDGs.

           Inference: Therefore, standardized mechanisms for sharing
                                                              5.9  Lack of awareness:
           incident data among stakeholders, including government
           agencies, industry partners, researchers, and the public, are  Observation: As mentioned in the previous paragraphs and
           lacking. It impedes collaborative efforts to address emerging  observed through Tables 4 and 5, the base of AI incident
           trends, root causes, and mitigation strategies for AI incidents.  reporting is narrow.

           Recommendation 6: Standardise data sharing mechanisms:  Inference:  The key stakeholders, including industry,
           Define protocols for data sharing, access controls, and  academia, civil society, the general public, and policymakers,
           privacy protection to ensure the confidentiality and security  are largely unaware of AI-incident databases.  Without
           of incident data. Establish mechanisms for sharing incident  active involvement from diverse perspectives, databases will
           data among stakeholders, including government agencies,  fail to capture the full spectrum of AI-related risks and
           industry partners, research institutions, and civil society  opportunities.
           organizations.
                                                              Recommendation 9:     Awareness programs:   Hold
           5.7 Sectoral underrepresentation:                  regular campaigns to enhance stakeholders’ awareness and
                                                              understanding of AI incident reporting standards and best
           Observation:   Existing  AI-incident  databases  have
                                                              practices.
           skewed   representations  of  application  sectors.
           "Media/entertainment/sports/art" sector has the highest  These standardization actions can enhance the effectiveness,
           number of incidents reported in AIAAIC, followed by  transparency, and accountability of AI-incident reporting
           automotive and politics sectors, as illustrated in Table 6.  processes, thereby contributing to the achievement of the UN
           Table 7 indicates that the maximum incidents reported  SDGs.
           in AIID relate to self-driving cars (Tesla, Cruise), social
           media (Facebook), search engines (Google), online shopping  It is further recommended to include incident reporting as
           (Amazon), and advanced AI models (OpenAI).         an integral part of the AI lifecycle so that it gets appropriate
                                                              focus in the future. Figure 1 illustrates the conceptualized
           Inference: While these databases predominantly report  AI lifecycle stages to collect data for developing incident
           consumer-oriented sectors, they underrepresent critical  mitigation strategies.
           infrastructure sectors such as telecom and electricity supply.
           The AI incidents in such sectors may not be as frequent as
           in the consumer-oriented sectors; however, it is still vital to    6.  CONCLUSION
           maintain a repository of their incidents.
                                                              In conclusion, this study highlights the critical need for
           Recommendation 7: Sector-specific AI-incident databases:  standardized AI-incident reporting to enable data gathering,
           Develop sector-specific AI-incident databases to supplement  research, and development of mitigation strategies for
           the general purpose AI-incident databases.         preventing future incidents. Through an analysis of existing
                                                              open-access AI-incident databases, it presents the key
           5.8  Demographic underrepresentation:              observations and gaps in standardization, underscoring the
                                                              importance of policy and standardization initiatives in this
           Observation: Table 8 shows that just three countries account  domain. Table 10 summarises the gaps observed and the
           for 60% of the incidents reported in AIAAIC. Similarly, the  recommendations to overcome them.




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