CODE-SPECIFIC: Why does using multiple PRNGs concurrently yield biased results?

import random as r
from random import Random
from threading import Thread
#ap = amount of random points
#load_split = how many threads are tasked with it
def pi(ap=1000000,load_split=16):
#circle hits
    c,=0,
#chooses a random point and sees if it is in the circle
    def t(seed,ap=ap/load_split):
        nonlocal c
        r = Random()
        r.seed(seed)
        while ap>0:
            if ((r.random()-0.5)**2+(r.random()-0.5)**2)**0.5<=0.5: c+=1
            ap-=1
    th = []
    for i in range(load_split):
        thr = Thread(target=t,args=[r.random()*i])
        thr.start()
        th.append(thr)
#executes the random tries lost to the threads
    for i in range(ap%load_split): 
        if ((r.random()-0.5)**2+(r.random()-0.5)**2)**0.5<=0.5: c+=1
#waiting for threads to complete
    for i in th: i.join()
    return 4 * c / ap
input(pi())

Why do the approximated pi values get smaller when I distribute the load over more threads?

First I thought it may be because of using the same seed, so I generate differently seeded local Randoms for each Thread, which each seed being randomised as well instead of just being incrementing integer values. (Even though I don't think the latter part made the difference)

But the problem still persists. Does anyone know the reason for that behaviour?