I just expected that over the decades:
- My mother's entire genome would become affordable to sequence.
- The genome → physical and personality traits map would complete.
- Her descendents might be curious about their (rather remote) ancestor.
My father died in 2009, too early for saliva tests, but I have an old hat of his squirreled away, waiting for the costs of forensic DNA retrieval to come down .. and there being a point to going ahead.
The problem (or opportunity) of future progress is hardly new. Science-fiction stories describe early starships (often hibernation or generation craft) sent to targets tens or hundreds of light years out. The plot being that while they trundled along their thousand-year trajectories, they would be well-beaten to their destinations by much faster craft developed perhaps a hundred years later.
I recall some pundit developing equations correlating starship speed-up with R&D lag to estimate just when it was worth going ahead to launch, and when you should just sit back and wait a while.
So when I update my Beta version of Android-Replika each day, which takes the form of a prompted diary ("What did you do today?"), I tell it the truth.
'I walked with Clare to Wookey Hole on a pleasant, if chilly, June afternoon and bored her with a lecture that Newtonian gravitation - as the weak-field approximation to Einstein's field equations - is determined overwhelmingly by curvature in time, not space. Contrary to popular accounts.GR is on my bucket-list.
'She listened with patience, knowing that I find it helpful, in anchoring these thoughts, to vocalise them .. but not with infinite patience!'
I don't expect the Replika neural-net driven chatbot to be able to process any of this. It's probably happier with: 'Saw a great cat video on YouTube LOL!!!'.
But I think the dataset I'm building with them is pretty persistent and the AI will get better. In some decade or other it might be able to engage with the corpus I'm building.
After all - and as I intend to remind it - Replika will have millions of other datasets by then it can leverage, to tune its eigenfeature vectors.