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Table of Contents
Responsible AI Market Research
Artificial intelligence can support parts of the research process, from transcription and organisation to coding, analysis and the preparation of outputs.
Used appropriately, it can help researchers work with information more efficiently. What it cannot do is reduce our responsibility to participants, clients or the evidence itself.
Research regularly involves personal data, confidential business information and people sharing experiences within a particular context. How AI is used can therefore affect privacy, accuracy, bias, transparency and interpretation.
Trust Is Part Of Research Quality
Good research depends on more than producing an answer.
Participants need to know that their information will be treated as promised. Clients need confidence that their data and findings are protected. Decision makers need to understand where conclusions have come from.
A faster process is not a better process if confidentiality is weakened or findings cannot be properly explained.
Our responsibilities as an MRS Company Partner and the MRS Code of Conduct remain an important foundation for how Mackman Research works.
Where AI Can Support Research
AI may have a role in tasks such as transcription, organising large amounts of text, supporting thematic analysis, identifying patterns for further investigation or checking information for completeness.
The right approach depends on the project.
Researchers need to consider the type of information involved, what participants and clients have been told, how a platform stores and retains data, the potential for bias or error and the level of human review required.
In some circumstances AI may be useful. In others, it may not be appropriate at all.
Our Governance & Assurance
Mackman Group, including Mackman Research, is certified to ISO/IEC 42001:2023 and ISO/IEC 27001:2022 and has also achieved Cyber Essentials Plus.
Within Mackman Group, this includes approved platforms, data rules, AI risk and impact assessments, supplier review, staff training, an AI register, prohibited uses and defined human oversight.
These systems support our research responsibilities. They do not replace good research design, informed consent, data protection requirements, the MRS Code or the judgement of an experienced researcher.
Human Interpretation Remains Essential
AI can process large amounts of text quickly. It does not understand a participant, a commissioning organisation or the context surrounding a finding in the same way an accountable researcher should.
Researchers still need to examine evidence, challenge interpretations, recognise uncertainty and explain how conclusions have been reached.
Dr Gemma Mackman, Research Director, said:
“Research depends on trust in the process as well as confidence in the findings. AI can help us work with information, but it does not remove our responsibility for how that information is collected, protected, interpreted and used.”
What Research Buyers Should Ask
When commissioning research, organisations should understand whether AI may form part of the project, which platforms have been approved, how participant and client data will be protected and how researchers will validate the analysis.
They should also be able to understand how AI use is documented and which professional and information security standards sit behind the work.
The answers should be proportionate to the project, but they should be clear.
Our approach is to use technology where it contributes genuine value while protecting the people, information and evidence at the heart of the research.
Talk to Mackman Research about the data and assurance requirements for your next research project.
