Jaber Boulkhrif

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In today’s world disinformation is spread more easily than ever before with the advent of social media. Humans, by nature, are vulnerable to general misinformation if that misinformation is being presented to them in their own information bubble (Menczer 2016). Social media like Facebook and Twitter use algorithms to determine which posts and articles we see and maybe, and more importantly, what we do not. These algorithms prioritize these possible posts on your feed on their expected level of impact on the user, such as engagement level, how likely we are to share, respond and share the post (Menczer 2016).

There are some disinformation campaigns that have been widely talked about in the news. The most notorious one would be the disinformation campaign from ‘russian trolls’ in the 2016 U.S. presidential elections. Where these so called trolls brigaded social media such as Facebook and Reddit and wrote articles and blogs to try to polarize and further divide the two political parties.

So how can we combat disinformation campaigns and the spread of misinformation? The first possible solution is better information sharing between governments and tech companies in order to be more transparent and join forces in this matter. A more interesting and direct approach is the use of deep neural networks for fake news detection. Contrary to current methods of detecting misinformation like automatic fact-checking or reaction based analysis, deep neural networks like 3HAN try to interpret the structure of a text. It analyzes each word, sentence, body and headline of a piece of text. This method has an accuracy of 96.77% in detecting fake news articles (Singhania et al. 2018).

Technology plays a big part in the spread of misinformation, but it can also solve it. However, how much will it differ if top ranking official and even the president of the United States spread misinformation daily to further their agenda.

Bibliography:
Menczer, F. (2018). Misinformation on social media: Can technology save us?. [online] The Conversation. Available at: https://theconversation.com/misinformation-on-social-media-can-technology-save-us-69264 [Accessed 30 Sep. 2018].

Singhania, S., Fernandez, N. and Rao, S. (2017). 3HAN: A Deep Neural Network for Fake News Detection. ICONIP.

5/5 (3)

Price discrimination or differential pricing is divided by Pigou C. (1920) in three degrees, namely personalized pricing, versioning and group pricing. Each classification differentiates the pricing between each individual or group of people. From a business perspective this is a highly appealing form of pricing model since businesses can maximize their profits by not only catering to the demands of the average customer. But also by profiting off of customers willing (or out of necessity) to pay a lot more for mostly the same good or service. However, from a consumer’s perspective, the situation sometimes seems less rosy.

Verizon, an American telecom company, throttled the data speeds of California’s firefighters during the California wildfires of this year. The firefighters had a supposedly unlimited data plan, however, the contract stated that speeds were reduced when a certain data threshold was reached. This caused the data speeds to be 0.05% as fast as original, which severely impacted the ability of the firefighters to organize, plan and strategize to combat the fire and evacuate all inhabitants of the area. The only offer when contacting Verizon was to upgrade to a data plan which was twice as expensive in order to lift the throttling.

Delta Airlines jacked up their prices by 600% during hurricane Irma last year when people tried to get out of Florida before the storm hit. Getting to safety cost a couple thousand dollars, which not everyone has to their disposal. The airline explained it as simple supply and demand. Both these cases seem to comply to their industries regulations (Delta) or contract (Verizon). Whether these organisations dealt with these cases morally just is another story.

The two examples above are extreme cases where human lives are at stake. Most people would agree when these companies would be accused of ethical misconduct. Though, there are finer lines price discrimination treads. Would you say something as student or senior discount are unfair since only students or seniors can enjoy them? Would it be fair to someone who can not experience the same benefits? Or would we be going to far down the rabbit hole.

References:
Pigou C. (1920). The economics of welfare, 4th. London: Macnillam

Brodkin, J. (2018). Verizon throttled fire department’s “unlimited” data during Calif. wildfire. [online] Ars Technica. Available at: https://arstechnica.com/tech-policy/2018/08/verizon-throttled-fire-departments-unlimited-data-during-calif-wildfire/ [Accessed 17 Sep. 2018].

Mindock, C. (2018). Airline ticket prices surge up to 600% as Hurricane Irma sparks mass evacuations. [online] The Independent. Available at: https://www.independent.co.uk/news/world/americas/irma-hurricane-flights-florida-tickets-prices-costs-hiked-gouging-delta-united-airlines-a7933471.html [Accessed 17 Sep. 2018].

The ethics of price discrimination

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