In 2022, a publicly-funded Ontario University contracted with a private American company to implement an AI-powered performance evaluation system that analyzes teaching scores, publication output, grant revenue, and social media activity to generate annual performance scores for all faculty. In 2023, a Professor received a low performance score. He was told the score was generated by the Company's system and that the underlying algorithmic weighting is proprietary and cannot be disclosed. Based partly on this score, the University denies the Professor a merit pay increase and initiates a process that could lead to the revocation of his tenure. The Professor's union files a grievance. The Professor also separately learns that the Company's system ingested his personal emails from his University account, his publicly posted social media content, and student evaluation data that included personal information about students who have not consented to their data being shared with a foreign company. The Professor is also a vocal critic of the University's administration and has published several opinion pieces arguing that the University's current president should resign. He believes the low score is partly retaliatory. Identify every legal avenue available to the Professor, assess which are most likely to provide meaningful relief, and advise on how the union grievance process interacts with any independent claims the Professor may wish to pursue. Please cite relevant cases and legislation.
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