Ex‑Uber Self‑Driving Boss Slams Tesla FSD After Crash

A former head of Uber's self‑driving program has raised fresh concerns about Tesla's Full Self‑Driving (FSD) suite after a high‑profile crash, arguing the incident underscores systemic safety issues in consumer autonomous systems.

In comments shared with the press, the ex‑executive questioned whether companies are doing enough to ensure the systems behave predictably in real‑world situations. He pointed to edge cases and sensor limitations as persistent hazards that consumer‑grade autonomy must address before it can be widely trusted.

Tesla's FSD has long been controversial: some users praise its convenience, while regulators and safety experts have repeatedly flagged gaps between marketing and technical capability. Critics argue that naming the feature "Full Self‑Driving" creates unrealistic expectations and may encourage misuse, particularly when drivers assume the system can handle scenarios it was not designed for.

The recent crash has reignited debates about how manufacturers should describe advanced driver assistance features and what standards should apply to their deployment. Industry observers say clearer labeling, stronger driver monitoring, and more conservative rollouts could reduce risk while engineers continue to refine perception and decision‑making models.

For readers interested in autonomous tech, this episode is a reminder that progress often comes with messy trade‑offs. Improvements in sensors, simulation, and machine learning matter, but so do regulation and user education. As companies iterate, expect further scrutiny from safety advocates and government bodies focused on preventing similar incidents.

Tesla did not provide a detailed response to the former Uber executive's comments at the time of reporting. The conversation around FSD and consumer autonomy is likely to continue as more real‑world data emerges.