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Making Algorithms Accountable to Citizens

Algoritmos que rinden cuentas a la ciudadanía

Paula Perez|

This piece is part of OGP’s “Open Algorithms Blog Series.” Read other posts in the series here.

Today, AI Now Institute, Ada Lovelace Institute and the Open Government Partnership (OGP) launched the first of its kind study that analyzes the initial wave of policy frameworks that promote transparency and accountability of governments’ use of algorithms across several jurisdictions. 

Since most of these policies are still in very nascent stages of implementation, the study covers early implementation trends rather than longer-term impact and provides guidance and lessons for policymakers responsible for implementation. You can find some of the key findings here and access the full report here

At RightsCon 2021, government officials and civil society organizations, including members of the Open Algorithms Network, discussed their experience implementing algorithm transparency initiatives and engaging the public in algorithmic policy. Here are some of the insights and challenges they shared, which contributed greatly to the findings of the report: 

  • Algorithms are complex and levels of public awareness vary. Because of heightened media attention across different countries and several scandals like in the Netherlands and the UK, people are becoming more aware and concerned about how public sector use of data and algorithms can significantly impact them.  But to go beyond that and achieve meaningful transparency and participation, it is important to make the information comprehensible to the public (such as France did by using a video to explain an algorithm), engage with affected communities on the design and implementation of algorithms, and provide concrete mechanisms for public scrutiny. Some of the early lessons of the public consultations implemented around the Algorithms Charter in New Zealand suggest there is a need to proactively engage with the public in early stages through workshops, the media, and partnerships with marginalized communities, as well as provide multi-phase feedback opportunities. 
  • There is a lack of shared or consistent language. Concepts like algorithms, automated decision-making and artificial intelligence are used with different meanings and understandings across jurisdictions and communities. As in all emergent policy areas, building a common understanding takes time, but to meaningfully engage citizens and to coordinate policy with the different government agencies that use algorithms, it is important to work towards overcoming ambiguity.
  • The availability and quality of the data shouldn’t be underestimated. The data inputted into an algorithm impacts the output of the decision on areas like health, education, public contracting, and others. Low quality data, that is produced with little or no oversight from the public, as well as missing data from specific groups (usually the most marginilized) can introduce bias and discrimination into algorithms and result in poor and discriminatory policy decisions. Efforts to improve the quality and availability of data need to be strengthened. 
  • The legal and policy frameworks that support the implementation of algorithmic accountability matter. Cross-cutting frameworks around areas like access to information, data protection regulation, digital infrastructure and accountability in administrative law, which vary across regional contexts and countries, can have an impact in the implementation of algorithmic accountability policies. This is especially important in contexts or countries where conversations around artificial intelligence and algorithmic policy are still in very nascent stages. As the use of algorithms in the public sector continues to increase, algorithmic accountability can also be looked at as a portal to discuss systemic issues related to foundational frameworks.

As we approach OGP’s 10th anniversary and with more than 100 countries and local members co-creating their action plans this year, OGP’s co-chairs have made a concrete call to action to all members to promote inclusive digital innovation in their action plan commitments. We hope that the lessons from this study and peer learning discussions can support the efforts of governments and civil society to advance algorithmic accountability, including as part of their OGP action plans.

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