There are several things you can do.
For example, say you wanted to hold the S&P500, but as individual stocks rather than paying someone at a mutual fund or ETF to hold it for you. This might be beneficial in a number of ways, but it has the serious drawback of having to manage 500 entries. You might already own a dozen or two of those entries already, or you have overlapping purchases in other investments.
You could tell a smart portfolio management program to use the S&P500 list as a target, and tell it about all the rest of your current holdings. Then it could analyze your current portfolio each day and make recommendations about how to get closer to your target, while avoiding wash sales and duplicate purchases. If you trusted that program, you could feed the output to your brokerage and have the trades executed automatically. Or you could look at the output and make decisions about whether you want to make the changes. Either way, you are no longer doing analysis yourself, and you're edging closer to your target, at which point you would be passive.
On the other hand, suppose you wanted an approximation of the S&P500 -- a target that would give you most of the same exposure and opportunity, but had a reduced number of individual stocks. You could run simulations on subsets of the S&P500 until you got a group that performed sufficiently similarly to the whole thing - 300? 250? 100? 50? as you reduce the set size you reduce the fidelity of the model - and then buy and hold those.
You can do a lot with an algorithm, and if your strategy doesn't need to operate in realtime, it will certainly look passive compared to HFT bots. A human might not want to rebalance more than annually or quarterly, because it can be a lot of work -- but a robot has no problems doing all the calculations daily and looking for a sufficient reward to present to you.