Diabetes management has steadily advanced along with the development of new technology. An important step in improving insulin delivery was the introduction of smart insulin pens that enhanced dosing accuracy and convenience of use. Smart Insulin Pens (SIPs) revolutionized diabetes care by introducing real time wireless connectivity, digital dose tracking, and integration with personalized dosing support. With automatic dose capture, reviewing insulin dose data became more effective, especially when paired with blood glucose data. This technology enabled patients, healthcare providers, and diabetes care teams to make data driven decisions and recommendations in real time. Improved diabetes management decisions became possible within a continuous and asynchronous framework with the use of SIPs. Manufacturers of insulin pens aim their efforts at further automation with more advanced software and integrated machine learning within SIPs. The role of technological advancements in diabetes care cannot be dismissed or undermined due to numerous benefits and opportunities modernized diabetes care carries. However, there are important challenges and vulnerabilities associated with technological advancements that this blogpost aims to discuss.

This research paper delves into the evaluation of two facial recognition software, one open-source and one paid version, Vladmandic and Visage SDK accordingly. Prior to the testing of a non-invasive Institutional Review Board (IRB) protocol involving 10 lab-team members in a lab environment, an initial hypothesis was formed suggesting that facial recognition software carries innate biases towards different demographics, ages, sexes, and physical traits. While external research supported these claims, the results of the protocol tests suggested otherwise. The tests probed the accuracy of detecting emotions displayed by the lab participants. Both software exhibited limited accuracy in detecting emotions, with Vladmandic achieving only 36% accuracy and Visage SDK reaching 50%. Shockingly, the results of the protocol testing reflected a contradictory conclusion to previous research, with demographic factors such as race, sex, and hair characteristics not significantly impacting the accuracy of the software. However, discrepancies in the experiment methodology and research protocol were noted, such as participant expression variability and subjective demographic data collection. This lab experiment emphasized the importance of refining research protocols and considering every potential external factor, such as lighting conditions, for the robust evaluation of facial recognition software. Additionally, the discrepancies between these findings and existing literature prompts a critical reflection of past external research, these series of tests, and the complexities of bias assessment in technological systems.

AI-based sentiment analysis has recently proven useful through the mining of large amounts of text. These texts can be drawn from various sources, but most valuably can be used to reach conclusions about public opinion, especially regarding current events. As a result, sentiment analysis provides a method for researchers to determine public opinion under authoritarian regimes through the medium of social media. Using social media allows researchers to find a closer approximation of genuine sentiment, as opposed to analysis of state propaganda or other strictly controlled media. This could be especially valuable in regards to Russia’s ongoing war in Ukraine, given the limited reliability of traditional opinion polling in a closed society. However, most sentiment analysis databases are drawn from English language texts, with relatively few based on Russian. This paper examines the existing scholarship on Russian-language sentiment analysis and its effectiveness when conducted based on social media texts, including the complications arising from the differing lexical structures of the language.

Digital autocracies leverage invasive technologies to carry out common authoritarian practices that aim to quell dissent, suppress democratic movements, and control their citizens through restricting their internet freedom. Azerbaijan exemplifies this through the documented surveillance of its dissidents. The social landscape of Azerbaijan disproportionately targets women through shame tactics that have transitioned to the online sphere. This transition marks the introduction of Azerbaijan’s newest campaign of censorship cementing spyware as a fundamental tool in maintaining Azerbaijan’s historical positioning as an authoritarian state. This work will aim to analyze how technology has taken on an increasingly determinant role in achieving a state’s control within the context of an autocratic regime; this point is supported by case studies of the repression of women in Azerbaijan.

India, the world’s largest democracy, faces a critical challenge in safeguarding citizens’ privacy rights amid the proliferation of invasive surveillance technologies. The troubling contradiction between India’s constitutional commitment to privacy and the government’s use of spyware like Pegasus to target journalists, activists, and opposition figures is examined. The Pegasus revelations expose the exploitation of legal loopholes and lack of oversight in India’s surveillance regime, enabling the unchecked abuse of power. Specific instances of surveillance overreach, such as the WhatsApp Pegasus Scandal of 2019 and the targeting of human rights defenders and journalists, demonstrate the chilling effects on free speech and dissent. By analyzing the gaps and deficiencies in India’s surveillance laws and practices, the urgent need for comprehensive reforms is underscored. The comparative analysis with the European Union’s data protection framework, using the Most Similar Systems Design (MSSD) method, offers valuable insights into balancing security and privacy concerns while upholding democratic principles. The critical importance of aligning India’s surveillance practices with its constitutional values and international human rights standards to safeguard the future of Indian democracy in the digital age is emphasized. Concerted efforts from civil society, policymakers, and the international community are called for to hold the government accountable and ensure the protection of citizens’ rights and freedoms.

Neurotechnology, the integration of technology with the nervous system, is an advancing field with potential medical applications by offering individuals with neuromuscular disorders or physical injuries an alternative means of communication beyond traditional verbal speech. One such advancement is the development of an electroencephalography-based brain-computer interface (EEG-based BCI) system, which functions to record and decode electrical signals from the brain into intelligible speech. While advancements in neurotechnology prove promising for assisting patients, this technology calls into question the ethical implications of cognitive translation that have yet to be explored in depth. As such, relevant publications investigating the efficacy and applicability of EEG-based BCI systems for brain-to-speech communication will be examined to determine the attitude of the scientific field regarding alternative communication technology and to assess the impact of this technology on cognitive privacy.

Internet censorship has long been a controversial issue which involves the selective restriction of information. This could simply be as mundane as upholding copyright laws, but censorship also extends into political repression and human rights violations. Restrictive and authoritarian regimes have been shown to be far more likely to suppress political content to subdue criticism. Russia has a particularly egregious reputation for censorship and restriction of speech online. Since 2012, the Kremlin has consistently acted to create legislation aimed at regulating online content and attempting to garner the support of the Russian people in doing so. This is significant especially because it has been found that Internet Literacy is negatively correlated with the perception of a necessity of government surveillance (people who are less familiar with the Internet tend to perceive a higher necessity of surveillance). The Russian government, then, draws attention to the dangers of the Internet and social media, including risks of hate speech, crime, violent protests and fake news. The government frames laws as protecting citizens and their rights from these threats. Furthermore, these threats are proclaimed to be both internal and external and are subsequently used to justify political repression through online censorship and strict controls that are characteristic of authoritarianism.

For as long as the TOR network has existed one of its primary uses has been the circumvention of Internet firewalls run by oppressive regimes. Iran is no exception to this trend, and in as early as 2011 Iran was the 2nd highest country by TOR users.1 There was even a point where TOR developers and the Iranian government ended up in a technological arms race as the government aimed to block the network while Tor developers simultaneously created new ways to circumvent said blocks, with developers even releasing same-day updates to counteract new restrictions.9 Iran has repeatedly been ranked among the worst countries in the world for press freedom, and it continues to offer little to no opportunity for Iranian citizens to access uncensored media on the Bright Web.11 In recent years, Iran has vastly improved its censorship technology, and Tor developers have been forced to react quickly to continue to provide access to Tor in Iran.

The Tor network provides unparalleled anonymity to its users. Using anonymity features on top of TCP, The Onion Router has proved useful for moderately low-latency tasks such as web browsing (Borinsov and Goldberg 2008). Tor networks operate through a network of thousands of decentralized, independently run nodes across the world. To connect to the network, a computer needs to be running the Tor browser. This browser will randomly connect to its first node, or relay. Each relay in the network only knows the location of the relay or computer immediately preceding and succeeding it. This process completely obfuscates the original computer’s location and makes it appear as if the computer’s IP address is the same as the Tor exit nodes. The connection will travel through three nodes before connecting to a web server- either outside the Tor network, such as a .com or .org top-level domain (TLD), or inside the Tor network- the .onion TLD. These .onion TLDs are known as Onion or hidden services and provide advanced anonymity features like hidden location and IP addresses, end-to-end encryption, automatically generated domain names, and website authentication between the user and the onion service. It can enable sites to be built that publish work without being worried about censorship (Jardine 2018).

Last week I arrived in Kyiv after 48 hours to planes and trains to a rain and snow mix falling on the Kyiv central train station. Men eagerly ran up to the arriving train carriages with flowers in hand to greet wives and girlfriends who had made the journey back to Ukraine. The train was entirely populated by women, children, and older men. The joy of reunion was conditioned by the reality of war. I have been coming to Kyiv for 20 years, first as a Peace Corps Volunteer, then as a research scientist for the United States Army Cyber Institute, and now as an academic from Virginia Tech invited to speak on the laws of war in cyberspace at the Kyiv International Cyber Resilience Forum at the request of Ukraine’s National Security and Defense Council (NSDC). The change in the city is palpable. It is a city both serving as the hub of the national idea of Ukraine, but also one that is clearly in and acutely impacted by the ongoing war.