Recurrent Neural Network (RNN) Vanishing gradient problem - Why does it affect earlier timesteps more?
Of course that all weights are the same, but the update applied to the weights has a contribution from each of the timesteps, and the contribution associated with the first timesteps is what is more affected by the vanishing gradient problem.