Dijital Tuğla - Bölüm 4: Makineler Kazaları İnsanlardan Daha mı İyi Önler?

16 Apr 2025 · 41 min
41:03

In this episode of the Dijital Tuğla podcast, hosts Cem Kafadar and Harika İllimler explore the promise and perils of using artificial intelligence to improve safety on construction sites. They begin by describing how AI‑enabled cameras, wearables, sensors and drones can monitor workers, detect fatigue, identify unsafe behavior and spot equipment anomalies before accidents happen, turning safety from a reactive to a proactive discipline. The conversation then shifts to practical challenges: bias in training data (age, gender, ethnicity) that can produce false alarms or overlook certain workers; the risk of over‑reliance on AI alerts that may halt projects unnecessarily; and the need for accurate, up‑to‑date data to avoid erroneous predictions. They discuss predictive maintenance examples, such as Japanese cranes detecting microscopic cracks, and highlight how AI can log and analyse massive safety data to inform strategic decisions and reduce insurance costs. Cybersecurity concerns are raised, including data manipulation, hacking of AI systems, and the legal/ethical liability when AI makes a wrong decision. Throughout, the hosts argue that AI cannot replace human judgment – it lacks contextual understanding, emotional cues and moral reasoning – and advocate for a hybrid human‑AI model where AI provides analysis and recommendations while humans retain final authority. They also touch on organizational culture shifts needed to adopt data‑driven safety models, the importance of proper calibration, trust building, and continuous training. The episode concludes with a teaser for the next show on drones in construction, emphasizing that technology must be paired with human insight to achieve safe, efficient sites.

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