2 things:

1. There is a common misconception that any threaded python code is slower than sequential. This is trivially false for IO-bound, and possibly, potentially, in some cases false for CPU-bound. Said interviewer had that very misconception.

2. More importantly - you and another parent are right. The code does not demonstrate what I thought it does. This is proven by removing the ThreadPool and leaving the code intact:

    import random
    import math
    from concurrent.futures import ThreadPoolExecutor as Pool

    items = [random.random() for _ in range(math.factorial(11))]


    def run(items, n):
        step = len(items) // n
        res = [sum(items[i*step : (i+1)*step]) for i in range(n)]
        return sum(res)

    if __name__ == '__main__':
        import timeit
        import sys
        n = sys.argv[1] if len(sys.argv) > 1 else 1
        time = timeit.timeit('run(items, %s)' % n, 'from __main__ import run, items', number=10)
        print("%s\t%.3f" % (n, time / 10))


    $ for x in `seq 1 11`; do python3 -m main $x ; done
    1       0.799
    2       0.749
    3       0.671
    4       0.715
    5       0.730
    6       0.704
    7       0.649
    8       0.631
    9       0.689
    10      0.613
    11      0.616

This is a result I'd have to silently contemplate before making any further comments.