Data and AI Ethics
Service module
Evinact helps organisations establish practical ethical frameworks for how data and AI are designed, governed and used.
We work with organisations to identify where ethical risks may arise, define appropriate principles and decision criteria and put controls in place to support responsible use.
Our approach focuses on the real-world consequences of data and AI decisions, including issues such as bias, fairness, transparency, accountability, human oversight and potential harm.
Ethics that can be applied in practice
Ethical principles are most useful when they influence real decisions.
Evinact helps organisations translate broad commitments to responsible data and AI use into practical governance, review processes and controls that can be applied across the lifecycle of a system or initiative.
Ethical principles and guardrails
We develop principles, decision criteria and guardrails that define what responsible use of data and AI means within your organisation.
These can reflect factors such as fairness, transparency, explainability, accountability, human oversight, safety and appropriate use, tailored to your sector, risk profile and operating environment.
Ethical risk assessment
We assess where data or AI initiatives may create ethical risks and what those risks could mean for individuals, communities and the organisation.
This can include examining potential bias, unequal impacts, inappropriate uses of data, limitations in transparency or explainability and whether suitable human oversight is in place.
Ethics embedded into governance
We integrate ethical considerations into governance frameworks, policies, approval processes and decision pathways.
This helps ensure ethical risks are considered alongside privacy, security, regulatory and operational risks when projects and systems are designed, approved and reviewed.
Responsible AI review and assurance
For AI initiatives, we can assess whether development and deployment practices align with the organisation’s responsible AI principles and risk settings.
This can include reviewing use cases, controls, accountability, oversight and the potential impacts of AI-supported decisions.
Roles, review points and escalation
We help establish clear accountability, decision-making responsibilities and governance pathways for ethical considerations, including when additional review is required and how concerns should be escalated.
Clear accountability helps avoid situations where significant ethical questions are recognised but no one has responsibility for resolving them.
Sector and community context
Ethical expectations depend on what the technology is being used for, who may be affected and the sensitivity of the decisions involved.
We tailor ethical frameworks and controls to the organisation’s operating context, including environments such as government, health and finance where data and AI may influence high-stakes decisions or services.
When you need data and AI ethics support
Data and AI ethics support can help when an organisation needs a clearer and more consistent way to assess the consequences of how data or AI is being used.
Common triggers include:
- AI is being introduced into decisions or services that could materially affect individuals or communities.
- Leaders need clearer principles or criteria for deciding which AI use cases are appropriate.
- Teams are concerned about bias, fairness, transparency or explainability in an existing or proposed system.
- Responsible AI principles exist, but there is no clear process for applying them to projects.
- Different teams are making ethical decisions inconsistently.
- New data uses raise questions that go beyond legal compliance or privacy requirements.
- Executives or governance forums need stronger assurance that ethical risks are being identified and managed.
- An organisation is working with sensitive data or providing services to people who may be particularly affected by poor decisions.
- Regulatory, policy or community expectations around responsible AI are increasing.
A practical ethics approach gives teams a consistent way to identify risks, make decisions and determine when additional scrutiny is required.
What you get from a data and AI ethics engagement
Clear ethical guardrails
Principles and decision criteria that define how data and AI should be used responsibly within your organisation.
Identified ethical risks
A structured view of potential harms, fairness concerns, transparency issues and other ethical considerations associated with particular initiatives.
Practical controls
Governance, review processes and safeguards designed to address ethical risks in day-to-day decisions.
Clear accountability
Defined roles, review points and escalation pathways so significant ethical issues have an appropriate owner.
Stronger assurance
A more defensible basis for demonstrating how ethical considerations are being identified, assessed and managed.
Ethics embedded into delivery
Processes that help teams consider ethical implications throughout design, development, implementation and ongoing use.
Why choose Evinact for data and AI ethics?
Evinact specialises in data, AI and digital. We give governments, businesses and communities the evidence they need to act.
Our ethics work is grounded in the decisions organisations are actually making and the people those decisions may affect. We focus on translating ethical principles into governance, controls and review processes that can be used in practice.
We also bring expertise across AI governance, privacy, data sharing, assurance and information management. That allows ethical considerations to be assessed alongside the broader risks and obligations that shape responsible data and AI use.
Our approach is proportionate to the potential consequences of the activity. A low-risk internal use case does not necessarily need the same level of scrutiny as an AI system influencing access to services or other high-stakes outcomes.
We can support organisations from the development of principles and frameworks through to implementation, review and assurance, helping embed ethical decision-making into existing governance and delivery processes.
Frequently asked questions
What is data and AI ethics?
Data and AI ethics is the practice of considering whether data and AI are being used in ways that are fair, responsible and appropriate, including the potential consequences for individuals and communities.
It can involve issues such as bias, fairness, transparency, explainability, accountability, human oversight, safety and appropriate use.
How is AI ethics different from AI governance?
AI ethics focuses on the principles and considerations that should guide responsible AI use.
AI governance establishes the structures, roles, policies and controls used to put those principles into practice and manage AI decisions and risks across the organisation.
The two are closely connected, and ethical requirements are often embedded within broader AI governance.
Is ethical AI the same as compliant AI?
No. Compliance asks whether an AI system meets applicable legal, regulatory or policy requirements.
Ethical assessment can consider broader questions, including whether an outcome is fair, whether people may be adversely affected and whether a use is appropriate even where it may be legally permitted.
How do you assess ethical risk in an AI system?
An ethical risk assessment examines how the system will be used, who may be affected and what potential harms or unintended consequences could arise.
This can include considering bias and fairness, transparency, explainability, accountability, human oversight, safety and the sensitivity of the decision being supported.
Do all AI projects need the same level of ethical review?
No. The level of review should reflect the risk and potential impact of the use case.
An internal productivity tool may require relatively light controls, while an AI system that influences high-stakes decisions about individuals may warrant much stronger assessment, oversight and assurance.
Can Evinact review an existing AI ethics framework or responsible AI principles?
Yes. Evinact can review existing principles, frameworks and governance arrangements to assess whether they provide enough practical guidance for real projects and decisions.
We can then refine the framework, strengthen controls and help embed the approach into existing governance and delivery processes.
Put responsible data and AI use into practice
Speak to Evinact about developing ethical principles, assessing risk and embedding practical safeguards into the way your organisation uses data and AI.
Related case studies
Australian Computer Society
Evinact supported the Australian Computer Society (ACS) to develop a fit-for-purpose IT Governance Framework aligned with its evolving organisational strategy and priorities.
State Government
Evinact provides independent assurance to support the effective management of public sector ICT investments and reduce the risk of failure. Our extensive experience conducting Gateway Reviews and Health Checks enables us to tailor each review to the client’s requirements while aligning with the Queensland Treasury and CDSB Assurance Framework.
Higher Education
Evinact was engaged by a Group of Eight (Go8) University to design and manage the migration of more than 50,000 in-flight student applications from a bespoke, university-built application platform to a third-party cloud solution.
