Mahalo takes a step forward with human-powered search engine
Jason McCabe Calacanis, CEO of Mahalo, believes that humans can outwit the machines. This is not a replay of Arnold Schwarzenegger's "Terminator" movies. Rather, Mahalo is a search engine that is powered by human judgment, known in Web 2.0 circles as "curation."
Context & Ripple Effects
Jason McCabe Calacanis has spent 2007 assembling Mahalo's bet that paid human editors can beat pure algorithms at search: a contributor program launched with the Mahalo Greenhouse in June, then the Follow toolbar in August, which injects Mahalo's hand-built result pages alongside whatever major engine a user is already on. A rumored $20 million funding round surfaced in August commentary but remains unconfirmed.
Today's step layers the social graph onto those editor-written results, so rankings reflect who a searcher knows as well as what staff curators produced. The skeptics are already on record — one August critique questioned the model, and a November analysis called it fundamentally flawed — making this release Mahalo's attempt to show curation can compound rather than stall.
First-order effects
- Searchers using Mahalo, or the Follow toolbar inside other engines' results, now see rankings shaped by their social connections stacked on human-edited pages — the product's differentiation against algorithm-only rivals changes as of this release.
- Calacanis converts months of infrastructure (Greenhouse contributors, toolbar distribution) into a single consumer-facing claim: judgment plus social signal beats the machine alone.
Second-order effects
- Because Follow distributes Mahalo's results inside the major engines' own interfaces, incumbents face pressure to explain why their listings carry no visible human or social judgment — competition moves from winning the query box to annotating someone else's results page.
- Scaling curation means scaling paid contributors, so Mahalo's cost per covered query becomes the metric its critics will watch; rival human-curation properties like Squidoo (the subject of unconfirmed speculation about competitive friction) sit directly adjacent to that labor economics.
Third-order effects
- If the pattern holds, search bifurcates into machine-scale indexing and human-judgment layers sold on top of it, with the economics of paid curators versus ad-funded algorithms deciding which structure survives.
- A curation-at-web-scale business effectively turns a search engine into a media editing operation, trading the marginal-cost advantage of algorithms for perceived quality — a trade regulators and advertisers have no established playbook for.
The trend: Search is turning into a contest over whether human editorial judgment and social signals can be layered onto algorithmic ranking — or priced competitively enough to replace it.