One of the really insidious parts of illegal logging is that the same criminal enterprises
are also engaged in trafficking drugs, weapons, and typically human trafficking as well. It's
not just damage to the environment where the trees were cut down, and it's not just the
source country losing those resources, it's also the fact then that those profits go on
to support these other kinds of international crime.
We're at a point in time where the
world's forests need all hands on deck, if we are not actively engaged in some form of
protection and some form of combating illegal logging, if we don't do it now, we may
not have a chance. We lose habitat that maybe we can never get back.
Internationally, we see the bulk of illegal logging happening in the tropics.
So we talk about deforestation,
illegal logging, land conversion in places like Congo, in sub-Saharan Africa, or the
Amazon in South America. The role that the US plays in the global illegal logging trade
is that we're a demand side, we're a consumer side of this problem. We know from research
and investigations that have been going on now quite actively for about 10 years, that
there's actually a lot more fraud and misrepresentation of forest products than people realize and
some of that material is doubtless of illegal origin. So when we're involved in the fight
against illegal logging, our role is really on this forensic timber identification piece.
This is the Center For Wood Anatomy Research. We're the home of the world's largest scientific
research wood collection. Everyone, I think, is familiar with forensics nowadays. One area
of forensics that people often overlook is botanical forensics. We'll work on whatever
cases that we need to. We've done plane crashes, we've done murder cases, we've worked on arson
cases, attempted car bombings. Since about 1999, one of the places that we've really
focused on heavily is using forensic wood anatomy to combat illegal logging. We develop
the technology and the tools for field deploying this kind of information so that field agents
can look at a paper and it says, "This is supposed to be species X. This is supposed
to be species Y." They need some kind of knowledge or technology to let them look at the wood
and see whether it lines up with the paperwork. And traditionally that's done by someone like
me, or I would train someone. And training human beings to do this takes a lot of time,
it takes a lot of effort. I really started saying, "How can we solve this problem of
needing to build this capacity and needing to get this information out, because I don't
think we can train human beings fast enough". And that actually led us down a pretty interesting
road of trying to come up with a technological solution to this problem.
It is essential to have an interdisciplinary team that knows about law enforcement, AI,
wood anatomy, and all these fields come together here. Alex is the wood anatomist, and he's
learned a little bit of machine learning from me. I'm a machine learner and I've learned
a little bit of wood anatomy from Alex. The Xylotron itself is this handheld, portable
device connected to a laptop to do wood identifications. The XyloTron is built from off the shelf components
and uses all open source technologies.
It has two primary components. It has the imaging device itself, which we call the xyloscope,
and then it has the laptop where we actually do the AI portion of it where the actual identification is made.
The biggest advantage is you can carry this thing in two hands and take it anywhere in the world.
That is not true of any of the other forensic technologies. They're really restricted to the laboratory.
The artificial intelligence model that we use in the XyloTron to identify wood is a neural network.
A neural network is basically
a mathematical computation, which has some numbers or knobs and parameters that can be
tweaked and changed in a data driven manner. In our case, the input is the image of a wood
and the output is going to be what species or what category this wood belongs to.
To operate this, all we have to do is have a specimen of wood and then place this flush
on the top surface there. Turning on the light, pressing this onto the surface of the specimen,
and then I have to orient the Xyloscope so that a certain botanical feature called "rays"
are running vertically in the image. It captures an image, it feeds that image into the system,
it breaks it down according to the machine learning algorithm, and then it gives me my
output. It's basically the exact same thing I see when I look with my hand lens at a block of wood.
There's always going to be this cat and mouse game between what the criminals
are doing and technology catching up with their misdeeds. Illegal logging is a global
problem, and to address it at a global scale, what we need is access to technology and expertise
that is scalable, affordable, and easy to adopt and adapt. The XyloTron project ticks
boxes on all these levels and it can be deployed at many different points in the wood supply chain.
In an ideal world, we would combat illegal logging in the forest. Right?
We would stop the people with the chainsaws.
And there are people out there trying to do that, but that's not a place where the science that we do here
can contribute much. If a shipment comes into the United States and we do the identifications
and it's illegal because they mis-declared what it was or because it's an endangered
species, we have the legal authority to seize that shipment. And if you can do that enough,
you're going to reduce the demand, you're going to reduce the degree
to which it's desirable to be out there illegally logging.
Because if they can't make money, they're not going to do it as frequently.
It’s just that simple.