Author Archives: shaniam

Is Antibiotic Resistance Our New Biggest Threat?

Throughout history, our advancements in medicine have allowed us to live longer, prevent the spread of certain infectious diseases, fight infections and overall improve our quality of life. However, in recent years some of the important medical breakthroughs we have made as a society have been threatened by antibiotic resistance.

What is antibiotic resistance? In short antibiotic resistance is when antibiotics become less effective at treating the desired infection. It is caused by bacteria who evolve to be able to resist the drugs intended to kill them, so without antibiotics to terminate them, these bacteria begin to flourish and can cause persistent infections which could potentially ultimately lead to death.

A comparative view of non-resistant bacteria and drug resistant bacteria. Image Source: flickr

According to a 2018 study, in 2018 antibiotic resistance rates in Canada were 26%. According to projected models an increase in antibiotic resistance rates in the future could severely impact Canada’s economy. The study states that if resistance rates were to increase to 40% and a possible worse case 100% by 2050, Canada’s economy would be smaller. It could cause a decrease in the employment force which is said to likely have the largest impact in labour intensive jobs. On a global scale, antibiotic resistance could also have severe socioeconomic consequences. It is believed that the cost of treatment for resistant bacterial infection could approximately be 700 US dollars. This will have the largest impact on those who have a lower income and could potentially increase the presence of a socioeconomic divide. So, aside from the obvious medical impacts of antibiotic resistance, there is the various associated issues that arise which can decrease societal progressions.

Currently scientists are attempting to find solutions to this serious threat. A biotechnology company called Genentech has recently had a team of scientists that have developed a drug that can more easily penetrate the cell membranes of certain bacteria. Additionally it proved to be effective against various multidrug-resistant forms of some of these bacteria. Although this drug development is in its early stages, it could be very impactful in reducing antibiotic resistance and solving some of the resulting issues.

 

Image Source: flickr

This week (November 18th– 24th) is considered World Antibiotic Awareness Week, which is important in spreading awareness to the public about how to effectively use antibiotics to mitigate potential increases in antibiotic resistance. Some common ways that you can decrease antibiotic resistance rates are:

  • Follow your medical prescription properly (don’t skip medication days)
  • Don’t take antibiotics for infections such as a cold or the flu
  •  Try to with the help of a doctor see if there are possible solutions to provide comfort aside from the use of antibiotics.

Simple steps like these can be impactful in decreasing antibiotic resistance rates and gives us the power to fight against this looming threat.

 

 

-Shania Mander

Deepfake Technology: Can you Tell what’s Real and Fake?

Artificial Intelligence (AI) has improved remarkably since its invention. It has a variety of uses from data analysis, robotics, and applications in the medical field. All these advancements have made impressive societal impacts, however are recent progressions in AI contributing more harm than good to society?

Generative adversarial networks (GAN’s) are a dual AI system which can simply be defined as AI’s which work against each other to improve each other. One AI system considered the generator, develops content and the other AI system determines whether it is fake or not. Every time the secondary AI correctly establishes that a generated piece of content is fake, it provides feedback to the generating AI so that it can improve at producing more believable content. This is an example of machine learning, as the AI systems are continuously bettering themselves from experience without the need to be specifically programmed. This AI technology is considered a neural network as it was created to resemble a human’s neural network, so that the computers will learn like humans.

This leads us to the question as to why GAN’s can be considered harmful? This is because GAN’s are used to create Deepfakes. The term deepfake is used to describe video and audio recordings which have been generated through machine learning. These videos are not real but can be very convincing.

The above video shows a side by side comparison of Robert De Niro and Al Pacino in the film Taxi Driver. In the original film Robert De Niro is the actual actor, however in this video through the use of deepfake technology the actor Al Pacino looks just as authentic as the lead.

                                                     Source https://en.wikipedia.org/wiki/File:Woman_1.jpg#filelinks

Another example of the power of GAN’s is the image above. The picture is a generated image from a GAN and despite how real or familiar this person looks the image is not of a real person. Sites such as “this person doesn’t exist”  are an entertaining way to witness the abilities of these GAN’s, as on this site every time you refresh the page a new generated image of a fake person is displayed.

For purposes like film production, the use of deepfake technology could actually be quite helpful, however it could also be used for much more damaging motives. Technology like this could be used for propaganda in political campaigns. For example videos could be produced of political candidates saying damaging words which would impact their campaign, however these videos could all be fake and a product of deepfake technology. This causes the overall manipulation of information. Additionally this causes a serious impact in the way information is communicated to the public. It also could potentially decrease the public’s trust in true information as it will become harder to decipher what is real from what is fake.

In a study earlier this year researchers had found that although currently it still takes technical skill and a team effort to produce realistic simulations of people’s faces, it is slowly developing to becoming a more automated and accessible technology. If a wider range of people have the ability to use this there are countless ways this technology can be applied; good and bad.

To prepare for this potential increase of deepfakes making its way online, we should be wearier and more critical of videos and information we are presented in the media and online. It is important for us to be aware of the presence of deepfakes so that we can be less susceptible to believing in false information.

 

 

-Shania Mander