Should AI Generated Behavioural Analysis Be Admissible in Parental Alienation Claims in English Family Courts?

Should AI Generated Behavioural Analysis Be Admissible in Parental Alienation Claims in English Family Courts?

Although AI is not currently an established tool for assessing parental alienating behaviour in English family proceedings, its potential application is increasingly credible. However, any use of AI generated behavioural analysis must remain subject to rigorous judicial scrutiny to preserve the welfare based and human centred nature of family justice. This article argues that AI could potentially assist with analysing digital evidence, but should not determine whether alienating behaviour has occurred.

Parental Alienating Behaviour and the Role of the Court

The terminology surrounding parental alienation is important. Cafcass, the Children and Family Court Advisory and Support Service, states that it does not use or refer to “parental alienation” as a condition or syndrome, instead using the term “alienating behaviours”. Its guidance emphasises that when a child resists or rejects a parent, the reasons for that behaviour must be explored. Domestic abuse or other harmful parenting must also be considered, and domestic abuse and alienating behaviours can coexist. In these situations, the court may take steps to restore the relationship with the rejected parent, while ensuring that the welfare of the child remains paramount and that the adults involved are safeguarded.

However, this poses the question of whether such behaviours can be easily detected using AI. An algorithm might identify repeated negative comments about a parent or patterns in communication, but identifying a pattern would not necessarily establish why that behaviour occurred. A parent communicating negatively about another parent could, for example, reflect harmful behaviour, but could also arise from genuine concerns about the child’s experiences. Cafcass therefore places the assessment within the wider consideration of the child’s welfare and circumstances.

This issue is reflected in Re C (‘Parental Alienation’; Instruction of Expert) [2023] EWHC 345 (Fam), where Sir Andrew McFarlane stressed the need for reliable and properly qualified expert evidence in parental alienation cases. He stated in paragraph 31 of the judgment that “The Family Court adopts a rigorous approach to the admission of expert evidence” and warned against evidence based on “pseudo science”. Although Re C did not concern AI, its emphasis on reliability raises an important question: can AI generated behavioural analysis meet the same standards required of human experts?

Is There Potential for AI Assistance in the Family Court?

In principle, an AI system could be designed to process large quantities of digital evidence, such as emails, text messages and records concerning contact between parents and children. It could identify recurring linguistic or behavioural patterns that might be difficult for a human to detect manually.

This could increase efficiency when reviewing evidence and reflects the growing integration of AI into professional practice. However, there is an important distinction between identifying a pattern and interpreting that pattern. AI might identify that a parent repeatedly refers negatively to the other parent, but it cannot simply infer from that pattern that alienating behaviour has occurred. Context and causation would still require human assessment.

Consequently, the strongest argument for AI would be for it to operate as an assistive tool, rather than as an independent decision maker. AI could flag potentially relevant evidence for consideration by a qualified professional, while the professional and ultimately the court would determine its full significance within each individual situation.

Could AI Satisfy the Rules on Expert Evidence?

Under section 13 of the Children and Families Act 2014, expert evidence in children proceedings requires the court’s permission. From 20 July 2026, the Family Procedure Rules also require expert evidence in certain children proceedings to be provided by a “regulated expert”, subject to exceptions.

This raises an important question for AI: if an AI system has no professional qualifications or regulatory status, can its analysis satisfy the standards required of expert evidence?

The Child’s Welfare

Ultimately, any use of AI must remain subordinate to the welfare principle. Under section 1 of the Children Act 1989, the child’s welfare is the court’s paramount consideration in the relevant proceedings. The court must consider the individual circumstances of the child rather than allowing an algorithmic assessment to determine the outcome.

This is particularly significant because Cafcass’s current approach requires consideration of why a child is resisting or rejecting a parent, including whether domestic abuse or other harmful parenting may be involved.

AI could therefore assist with processing evidence, but it should not replace the court’s evaluation of the child’s individual welfare. Human centred decision making, alongside the use of a posteriori analysis through AI and other digital databases, may become part of the future of family court proceedings.

Conclusion

AI generative tools may play a vital role in aiding analysis in various family court matters, including parental alienation claims. However, the better approach would be to treat AI as an assistive analytical tool rather than an independent expert or decision maker. Given the risks of hallucinations, bias and unreliability, any such use must be subject to rigorous scrutiny by qualified professionals. Ultimately, the decision as to whether alienating behaviour has occurred and what arrangements are in the child’s best interests must remain a matter for the court, with AI serving only as an additional tool.