Data and artificial intelligence ethicist

You can:

• collate, analyse and evaluate qualitative and quantitative data and information, with support
• turn simple data into clear findings
• involve others in analysis and synthesis to increase consensus and challenge assumptions, with support
• help define project outcomes and ethical considerations

You can:

• incorporate a wide variety of views from underrepresented groups into product and policy work
• identify consequences of technology systems on a diverse range of stakeholders
• collect and use complex insights on social issues, types of bias or discrimination faced by different groups to inform your team’s work

You can:

• explain concepts from social science, such as anthropology, economics, sociology, philosophy, psychology or race theory
• explain how some social science theories can be applied to inform data and AI projects, products and policies

You can:

• communicate effectively with technical and non-technical stakeholders
• support and host discussions within a multidisciplinary team, with potentially difficult dynamics
• be an advocate for the team externally
• manage differing stakeholder perspectives

You can:

• clearly explain how simple technology and data products and services are built
• support communication with data science experts on ethical issues related to their work
• support data scientists and engineers in implementing data and AI ethics, under guidance

You can:

• describe some data and AI ethics tools that can be used by organisations
• describe some product management principles and approaches relevant to data and AI ethics
• explain the importance of being able to quickly adapt to new ways of working

You can:

• apply fundamental principles of data ethics and privacy in your work under supervision
• share data ethics and privacy risks through appropriate channels

You can:

• identify technical disputes and describe them in ways that are relevant both to direct peers and to local stakeholders
• generate multiple solutions to a problem and test them
• work collaboratively while recommending decisions and the reasoning behind them

You can:

• investigate problems in systems, processes and services, with an understanding of the level of a problem, for example, strategic, tactical or operational
• contribute to the implementation of remedies and preventative measures

You can:

• describe who your stakeholders are and the importance of managing relationships with them
• explain what your stakeholders find important and why

You can:

• collate, analyse and evaluate qualitative and quantitative data and information, with support
• turn simple data into clear findings
• involve others in analysis and synthesis to increase consensus and challenge assumptions, with support
• help define project outcomes and ethical considerations

You can:

• incorporate a wide variety of views from underrepresented groups into product and policy work
• identify consequences of technology systems on a diverse range of stakeholders
• collect and use complex insights on social issues, types of bias or discrimination faced by different groups to inform your team’s work

You can:

• apply social science theories to inform data and AI projects, products and policies, with support
• evaluate and challenge assumptions made in data science projects, with support
• work effectively with stakeholders in applied social sciences, such as academics and external researchers

You can:

• listen to and interpret the needs of technical and non-technical stakeholders, and manage their expectations
• manage active and reactive communication
• support or host difficult discussions within the team or with diverse senior stakeholders

You can:

• clearly explain how complex technology and data products are built
• clearly communicate appropriate ethical considerations related to data and AI systems, such as bias and responsible governance, to other disciplines
• support data scientists and engineers to implement data and AI ethics effectively

You can:

• support the development of data and AI ethics tools
• use product management principles and approaches, with support
• contribute to defining deliverables and evaluating products
• support the promotion of products

You can:

• work with stakeholders to identify and address ethical and privacy concerns
• demonstrate and communicate how data ethical issues fit into the wider organisational context
• research developments in data ethics and privacy to improve compliance and processes
• assess and constructively challenge proposed data ethics policies

You can:

• identify technical disputes and describe them in ways that are relevant both to direct peers and to local stakeholders
• generate multiple solutions to a problem and test them
• work collaboratively while recommending decisions and the reasoning behind them

You can:

• initiate and monitor actions to investigate patterns and trends to resolve problems
• effectively consult specialists where required
• determine the appropriate resolution and assist with its implementation
• determine preventative measures

You can:

• identify important stakeholders and communicate with them clearly and regularly
• tailor communication to stakeholders' needs and work with them to build relationships while meeting user needs
• build and reach consensus with stakeholders
• work to improve stakeholder relationships using evidence to explain decisions

You can:

• use the most appropriate methods to collate, analyse and evaluate qualitative and quantitative data and information
• quickly draw out the most relevant information from a range of complex sources
• involve others in analysis and synthesis to increase consensus and challenge assumptions
• help teams integrate ethical diagnostics and assessments

You can:

• use in-depth consulting and outreach strategies to influence organisational plans and goals
• lead others in determining the consequences of technology systems on a diverse range of stakeholders
• set best practice and direction on collecting and using insights on social issues, types of bias and discrimination different groups can face

You can:

• describe emerging or complex theories and concepts in social sciences
• apply social science theories to inform data and AI projects, products and policies
• evaluate and challenge assumptions made in data science projects
• lead work with stakeholders in applied social sciences, such as academics and external researchers

You can:

• listen to and interpret the needs of technical and non-technical stakeholders, and manage their expectations
• manage active and reactive communication
• support or host difficult discussions within the team or with diverse senior stakeholders

You can:

• clearly explain technical data and AI ethics issues with stakeholders at all levels, and from any discipline
• effectively answer challenging questions on how complex technology and data products are built
• guide others in how to effectively communicate complex data and AI ethical considerations

You can:

• develop data and AI ethics tools that translate theoretical principles into practice
• use appropriate product management principles and approaches for data and AI ethics tools
• capture and translate user needs into deliverables
• implement feedback gathering, evaluation mechanisms and product promotion

You can:

• work with stakeholders to identify and address ethical and privacy concerns
• demonstrate and communicate how data ethical issues fit into the wider organisational context
• research developments in data ethics and privacy to improve compliance and processes
• assess and constructively challenge proposed data ethics policies

You can:

• work with consequential or complex risks
• build consensus between services or independent stakeholders
• lead others to make good design decisions
• apply different risk methodologies in proportion to the risk

You can:

• ensure that the right actions are taken to investigate, resolve and anticipate problems
• co-ordinate the team to investigate problems, implement solutions and take preventive measures

You can:

• work with the team to develop and maintain an understanding of stakeholders
• work with the team to develop and implement stakeholder communications strategies
• identify and resolve issues, influence stakeholders and manage relationships effectively
• build long-term strategic relationships and communicate clearly and regularly with stakeholders

Communicating between the technical and non-technical

Stakeholder relationship management

Data ethics and privacy

Problem management

Communicating between the technical and non-technical

Communicating between the technical and non-technical

Data ethics and privacy

Problem management

Communicating between the technical and non-technical

Problem management

Communicating between the technical and non-technical