The team from Wildlife.ai has been pondering whether biodiversity credit systems (BCS) offer a real solution to biodiversity loss or are just a greenwashing tool for corporations. This opinion post summarises our discussions and thoughts.

Ai-generated image of an animal

(c) Deep.Ai ‘a rare animal is staring cautiously at a pile of money’

The New Zealand government has recently asked for feedback on a potential biodiversity credit system, and the Wildlife.ai team researched if this initiative would be a good solution for tackling biodiversity loss.

At first, discovering the concept of biodiversity credit systems (BCSs) got us genuinely excited. It seemed that handling the complexity of biodiversity credits aligned well with our skill in harnessing the power of AI for conservation. But, as we delved deeper, more and more questions came up.

Similar but different

A primary concern with BCSs revolves around measuring their impact accurately. The emergence of BCSs as a “similar but different” tool to the carbon credit systems made us uneasy. The current carbon offset system appears to be ineffective (breaking record temperatures both on land and sea), and its impact is much easier to measure.

We have not found (yet) robust methods to assess the lasting effects of conservation efforts through biodiversity credits. Ecosystem restoration can’t be simplified to isolated actions like planting 10 acres of native forest; instead, it requires locally specific and holistic assessment over an extended period.

Not having a solid way to measure makes it hard to tell if biodiversity credits are really helping conservation or not. To ensure BCSs are effective, we need scientific and simple methods to assess how well they work over time. Notably, most of the proposed initiatives don’t thoroughly address these methods and seem to be adopting solutions before they have identified the problems in question.

Sharpening the focus

Currently, the emphasis appears to be on landowners securing funds for their conservation projects and companies using credits to offset their activities. However, the discussion needs to surpass this binary perspective – it’s not merely about a farmer aiming to transform part of their property into native ecosystems and a company willing to finance it. We should remember that local communities also merit financial support for their often-overlooked restoration work.

We believe the focus should be pivoted towards prioritising the needs of local ecosystems and communities, including indigenous people and their lands. We need to start from the grassroots up to develop long-lasting solutions, rather than the other way around.

AI generated bird image

(c) Imagine.art ‘a rare animal is staring cautiously at a pile of money’

Bound by Law or Bound by Choice?

It is early days for BCSs and there is still no clear consensus on whether the system should be optional or mandatory. If they remain voluntary, their effectiveness will rely on the enthusiasm and popularity of biodiversity, potentially resulting in a volatile and unstable market. On the other hand, if biodiversity credits become mandatory, there’s a risk of corporations using them to keep on business as usual and diminishing current environmental regulations. BCSs could unintentionally contribute to greenwashing, diverting attention from the genuine needs of ecosystems and communities.

The solution could be a mixed model, where governments incentivise BCSs and ensure environmental claims and actions are strictly aligned with local and global biodiversity goals.

AI and biodiversity credits

We foresee artificial intelligence (AI) systems to be critical for the success of potential BCSs. AI excels at translating complex and diverse data into simple information, so AI could be useful in measuring a biodiversity unit or credit that is relevant to the local, regional and global conservation needs. AI’s ability to model biodiversity under different scenarios and analyse information in real-time will also be advantageous to build resilience and stability in the BCSs. However, common concerns with the use of AI, like bias, explainability, and security, will also apply to the potential use of AI for biodiversity credits.

Keep conservation simple

It is easy to get lost in the technical details and all the what-if scenarios for BCSs. So, we believe that if the aim is to increase the funds corporations contribute to ecosystem protection and restoration, perhaps the ideal approach would be to directly finance environmental NGOs and local communities. Companies, of all sizes, are already positioning ahead in the market by directly financing and supporting environmental conservation. Yes, we know it’s not enough but perhaps there are other ways to incentivise consumers to purchase products and services from companies that demonstrate a strong commitment to environmental responsibility.

Understandably, companies supporting biodiversity initiatives want assurance that their financial contributions have a real impact, but what would be the cost and conservation impact of creating, implementing and maintaining BCSs?

AI generated animal image

(c) YouCam ‘a rare animal is staring cautiously at a pile of money’

Summing Up

Biodiversity credits hold the promise to be more effective than carbon credits. Their ultimate goal is to incentivise more businesses to fund biodiversity conservation and restoration projects. Most of the impact of BCSs, so far, has been kickstarting conversations and discussions. For example, In Aotearoa New Zealand, a public consultation exploring whether BCSs could help nature has just concluded. We will watch this area with interest and look forward to engaging in future discussions, particularly on the potential role AI systems could play to ensure a BCS is transparent, efficient and effective.

We invite everyone globally to participate in the conversations, consultations and discussions. We hope that together we can answer some of the questions posed here.