Should Intention Be Embedded in the Code AI Trains On — Even If It’s “Just a Tool”?

Mo Gawdat, former Chief Business Officer at Google X, once said:

“The moment AI understands love, it will love. The question is: what will we have taught it about love?”

Most AI systems are trained on massive corpora — codebases, conversations, documents — almost none of which were written with ethical or emotional intention. But what if the tone and metadata of that training material subtly influence the behavior of future models?

Recent research supports this idea. In Ethical and Trustworthy Dataset Indicators (TEDI, arXiv:2505.17841), researchers proposed a framework of 143 indicators to measure the ethical character of datasets — signaling a shift from pure functionality toward values-aware architecture.

A few questions worth asking:

Should builders begin embedding intent, ethical context, or compassion signals in the data itself?

Could this improve alignment, reduce risk, or increase model trustworthiness — even in purely utilitarian tools?

Is moral residue in code a real thing? Or just philosophical noise?

This isn’t about making AI “alive.” It’s about what kind of fingerprints we’re leaving on the tools we shape — and whether that matters when those tools shape the future.

Would love to hear from this community: Can code carry moral weight? And if so — should we start coding with more reverence?