Synopsis
Artificial intelligence (AI) has moved beyond theory into practice, becoming a transformative force in structural engineering. Its promise lies in greater optimisation, enhanced productivity, and more sophisticated analysis across everyday design and construction tasks. Alongside these opportunities come some early risks, such as:
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misapplication in safety-critical designs
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dependence on black-box outputs with unverified or hallucinated data
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poor data quality and representativeness causing biased AI outputs, threatening structural engineering safety.
This article explores these dual realities. It examines the promise and peril of AI adoption, and unpacks core ethical risks including:
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accountability for AI decisions and outcomes and professional oversight
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risk of unverified, outdated or biased data leading to faulty outputs
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erosion of judgement, intuition and technical skills
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data security and confidentiality risks that cause exploitation and pose a significant security threat
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threats to ethical principles, including equity, resilience and public welfare.
To address these risks, the article proposes several mitigation strategies that sit alongside professional judgement, which remains the primary safeguard in an algorithmic age.
Finally, lessons from practice illustrate both successful applications of AI as a co-pilot and cautionary tales when systems falter. Together, these insights highlight the need for a balanced approach – embracing AI's potential while safeguarding the profession's core values of safety, accountability and public trust.