GMOs and QR Codes: Consumers need more than a label they need a learning path

I recently came across an article in national geographic about the new GMO labeling compromise that I thought was well written:

http://www.nationalgeographic.com/people-and-culture/food/the-plate/2016/07/gmo-label/  

The article asks:

"But what good is a label if people don't know what it means?"

That's the point...a blatant politically charged label with direct language or terms like "genetically engineered" is meaningless. I've discussed before how this can increase information asymmetry (i.e.consumer confusion).

One thing the article discusses is the huge gap in the science related to biotechnology and consumer knowledge and perceptions (something I have been studying since graduate school):

"Despite thousands of scientific studies, support from the World Health Organization, the American Medical Association, and the National Academy of Sciences, and, most recently, the concerted advocacy of 107 concerned Nobel laureates, the bulk of the public remains firmly convinced that GMOs are at best undesirable and at worst, downright dangerous. In other words, to the majority of Americans, a GMO label on a can of corn might as well be a skull-and-crossbones. What we’ve got here is a gaping divide between reputable scientific research and public perception. Unfounded GMO fear-mongering is doing us, as a planet, more harm than good."


There is huge burden on the consumer in terms of understanding complex modern agriculture. Earlier in the article there is some criticism of the currently proposed labeling paradigm:

"The federally approved warning label can consist of a QR (Quick Response) code, accessible by smartphone, or an 800 number that customers can call for information. These alternatives are not immediately helpful, and require time and effort on the part of consumers, many burdened with long grocery lists and fractious toddlers."

But given the huge gap in information I'm not sure there is any label that can be immediately helpful. The last thing we need is a shortcut label with confusing language like "genetically modified" that information economizing consumers will just interpret as a skull and cross-bones and move on. That approach is no better. It may in fact be the case that the QR code, if implemented properly may be the best way to attempt to fill that gap. It accomplishes a couple important things:

1) It can provide full disclosure and transparency
2) For consumers that truly want to understand what is in their food, it *can* potentially provide a learning path that helps fill this gap of knowledge from farm to fork

As I understand it, the details around the content and format of information related to QR codes is yet to be decided. I think a few things are necessary to make this work.

First, if this issue is important enough to be addressed FEDERALLY with a national labeling standard, then lets make this work for all food. Maybe require in some format that all foods that fall under this legislation have a "more information" section and a QR code, not just foods that contain so called "genetically engineered" ingredients.  If a label with a QR code becomes a proxy indicator for GMOs, that will defeat the whole purpose of an effort genuinely designed to inform the consumer. After all there are lots of approaches to food production out there- conventional breeding and hybridization, recombinant DNA, mutagenic approaches, and on the horizon CRISPR cas technology (HT: John Phipps).

Second, what should the 'landing page' look like for a QR code? What kind of information should it contain and how should it be presented? This is where the government needs to elicit the help of experts in science and communication. I am not sure, but I propose a learning path. Before saying anything about how a specific food product was produced, the consumer should quickly and effectively be exposed to a summary or survey of the many ways plants and animals are modified in agriculture to produce the foods we have today. (again conentional breeding/selection/hybridization/mutagenic/recombinant/CRISPR cas9/fermentation/cheese cultures etc.). Also they should be informed about the safety, regulations etc. about these technologies and the consensus views of groups like World Health Organization, the American Medical Association, and the National Academy of Sciences etc.

Finally they should be informed about the specifics of the food they are considering to purchase. All of this info can be standardized and used as stock for all food products, with more specific information for each food product detailed at the end of the 'learning path.' Maybe this could all be accomplished with a video or interactive infographic. But I firmly believe that a more comprehensive universal learning path approach like this is the most honest and transparent way to inform consumers about current and new technologies on the horizon and their safety and benefits. Not some politically loaded unscientific term like "genetically engineered" or "genetically modified."

An Econometric and Game Theoretic Analysis of Producer and Consumer Preferences Toward Agricultural Biotechnology

It is no secret these days that there are anti-biotech activists that reject the science related to the safety and benefits of biotechnology but yet have no issues accepting the science related to climate change or other fields. In my early days, back in graduate school I hypothesized that beliefs about the safety of biotechnology were more related or driven by political constructs than knowledge or acceptance of science itself. This was crude (I wish I had the floppy with the actual paper...and a drive to read it) but my general findings were that those that believed in climate change or were supportive of stem cell research were less likely (45-50% less using the divide by 4 rule for marginal effects) to believe in the safety of biotech foods. 

Of course this work had some drawbacks, including small sample size and power. But also, after a few years on the job and working on a limited basis with structural equation modeling, there are more powerful methods I could have used looking at these effects. But I think it was an interesting preliminary finding that seems to still hold true almost a decade later.

See also:

Perceptions of GMO Foods: A Hypothetical Application of SEM 

Left vs Right Science vs Risk vs Propensity to Regulate 

Monsantophobia Explained

Reference:

Matt Bogard. "An Econometric and Game Theoretic Analysis of Producer and Consumer Preferences Toward Agricultural Biotechnology" Western Kentucky University (2005)
Available at: http://works.bepress.com/matt_bogard/31/

 Abstract:

Agricultural biotechnology offers tremendous benefits to farmers and to society as it provides tools for mitigation of a number of environmental externalities related to water quality, food safety, and climate change. However, perceptions of the safety of recombinant DNA technology on the part of consumers and management decisions by producers can shape the policy environment in ways that may inhibit expanded use of biotech traits in agriculture. This presentation presents a summary of results from an econometric and game theoretic analysis of consumer perceptions and producer decisions as they relate to agricultural biotechnology.

Submitted in partial fulfillment of AGRI 597 Independent Study/Special Problems in Agriculture.

CRISPR Technology

A nice article related to CRISPR technology and an application with waxy corn in a recent DTN article:

https://www.dtnpf.com/agriculture/web/ag/news/article/2016/06/17/gene-editing-comes-agriculture 

A very nice description of CRISPR technology:

"The letters CRISPR stand for "clustered regularly interspaced short palindromic repeats," that is, snippets of DNA….They work as part of the bacteria's defense system, in partnership with a group of special, DNA-cutting Cas ("Crispr-associated") proteins and RNA molecules….When viruses invade, the bacterial CRISPR-Cas copies DNA sequences from the virus and saves this information as a short CRISPR repeat -- a sort of molecular mug shot. When that virus invades again, these repeats are remobilized as RNA molecules, which recognize the virus DNA sequence and guide the CRISPR complex to it. There, the Cas protein snips the offending DNA sequence out, disabling the virus."

"Using a specific protein, Cas9, researchers are now using this CRISPR complex to target specific genes in the genome of plants, animals and even humans. The RNA guides the CRISPR complex to the gene sequence in question, and Cas9 cuts it out. Researchers can leave the DNA to heal on its own or they can insert a desired gene in its place."

The article goes on to discuss the regulatory environment and applications related to a new variety of waxy corn in the development pipeline for Pioneer.

Left vs Right Science vs Risk vs Propensity to Regulate

Jayson Lusk has an interesting post on his blog related to an article in the Journal of Agricultural and Resource Economics finding an interesting relationship between left leaning voters and their willingness to support GMO labeling initiatives:

“One distinction, which I think is missing, is the greater willingness of those on the left to regulate on economic issues, such as GMOs, than those on the right. Stated differently, there are questions of science: what are the risks of climate change or eating GMOs. And then there are more normative questions: given said risk, what should we do about it? Even if the left and the right agreed on the level of risk, I don’t think we should expect agreement on political action.”


If I understand this correctly, I think this implies that if both those on the left and right agreed that there was some 'day after tomorrow' scenario (in terms of climate change) that warranted some type of government intervention, and they agreed that the science says there is a 3% chance of it happening without the intervention, then those on the right might object to the intervention for that given level of risk while a more left leaning person would support it. A right leaning person might suggest more market based alternatives or taking the gamble. But perhaps if the risk were higher, they might support doing more. In other words there might be different thresholds for the level of risk required to support a given policy interventions across the political spectrum.

Of course, the scientific consensus on climate change may not really even be strong enough to know for sure, i.e. the science isn't settled on exactly what scenarios are likely to play out and the probabilities that they will occur. There's a lot of science to support a wide range of probabilities and scenarios based on a number of assumptions. (see here,  here, here, and here). So really, I think even the science, risk, and potential outcomes or scenarios are largely based on perceptions and these might actually differ significantly across the political spectrum. Maybe its really about perceived risk.

Just thinking about this a little more what if we specified a model of preferences toward government intervention like that below (this is more an illustration than a serious attempt to look at this empirically):

Pr(SUPPORT POLICY) =  B0 + B1 PERCEIVED RISK + B2 KNOWLEDGE

So if we estimated simple linear probability models as specified above for democrats and republicans (as short hand for political preferences) according to the story line above B1 would be higher for democrats than republicans. (I'm ignoring the use of interaction terms on purpose for simplicity) I wonder if this would also be true for B2, for a given level of knowledge, would B2 be higher for democrats/liberals? I also wonder if PERCIEVED RISK is really a function of KNOWLEDGE? Maybe a different specification would look something like:

Pr(SUPPORT POLICY) = B0 + B1 PERCEIVED RISK(KNOWLEDGE)

where PERCEIVED RISK = f(KNOWLEDGE)

So in this case perhaps B1 would still be higher for those with more left leaning politics. Still I wonder, besides this effect, what if its the case that the level or mean of PERCEIVED RISK is in general higher for those on the left? So you have this effect of a greater inclination for a preference for government intervention given a level of PERCEIVED RISK (via B1) but also a population of left leaning voters with a PERCEIVED RISK levels that are on average some magnitude higher. Both of these effects would likely increase the propensity of supporting government intervention.

Consider also....if PERCEIVED RISK = f(KNOWLEDGE), is the level of KNOWLEDGE about GMOs or climate change the same for those on the left and right and is this really what is partly determining different levels of PERCEIVED RISK?  I'm not sure....how often do we hear arguments from the left that drastic actions or mitigating policies to combat climate change are necessary because of the scientific consensus on climate change when in fact the consensus as it is is pretty weak. Too weak to offer much guidance on actions, or very precise estimates of actual risks. (again see here,  here, here, and here). And even some of the world's leading experts in risk modeling tend to have some ideas about GMO risks that can be seriously questioned (see here). There was a really good book a few years back discussing voter preferences and systemic bias regarding economic policy that addressed similar issues (see The Myth of the Rational Voter).

If preferences toward policy can be modeled in this way, an interesting and maybe promising feature is that perhaps the level of knowledge feeding into PERCEIVED risk can be altered. We often hear that science and evidence rarely will change minds when it comes to biotechnology or climate change, however, in a paper recently published by the Journal of the Federation for American Societies for Experimental Biology (FASEB) Jayson and Brandon McFadden observed the following:

1) consumers, as a group, are unknowledgeable about GMOs, genetics, and plant breeding and, perhaps more interestingly

 2) simply asking these objective knowledge questions served to lower subjective, self-assessed knowledge of GMOs (i.e., people realize they didn't know as much as they thought they did) and increase the belief that it is safe to eat GM food. 

I'm not  a PhD Economist or Psychometrician but I would think an approach similar to the structural equation modeling framework I discussed before (depicted below) might get closer to specifying and measuring all of the causal paths and connections between latent constructs around risk perception and the policy environment for GMOs or climate change. Of course that would also require a solid data set and valid survey instruments. Jayson's work seems to be leading the way. These are just my initial thoughts prior to even reading the Jayson and McFadden article or the JARE article mentioned above and honestly I have not reviewed much of the actual literature or survey analysis related to risk and perceptions or policy preferences since graduate school. Maybe a lot of this has been done already.

(click to enlarge)