Using incognito mode and VPN may still not ensure total privacy, according to expert

Introduction

The first activity one engages in while using social media is scrolling through their feed and liking or reacting to posts. Social media users' online activity is passive, involving merely reading and observing, while active use occurs when a user consciously decides to share information or comment after actively analysing it. We often "like" photos, posts, and tweets reflexively, hardly stopping to think about why we do it and what information it contains. This act of "liking" or "reacting" is a passive activity that can spark an active discourse. Frequently, we encounter misinformation on social media in various forms, which could be identified as false at first glance if we exercise caution and avoid validating it with our likes.

Passive engagement, such as liking or reacting to a post, triggers social media algorithms to amplify its reach, exposing it to a broader audience. This amplification increases the likelihood of misinformation spreading quickly as more people interact with it. As the content circulates, it gains credibility through repeated exposure, reinforcing false narratives and expanding its impact.

Social media platforms are designed to facilitate communication and conversations for various purposes. However, this design also enables the sharing, exchange, distribution, and reception of content, including misinformation. This can lead to the widespread spread of false information, influencing public opinion and behaviour. Misinformation has been identified as a contributing factor in various contentious events, ranging from elections and referenda to political or religious persecution, as well as the global response to the COVID-19 pandemic.

The Mechanics of Passive Sharing

Sharing a post without checking the facts mentioned or sharing it without providing any context can create situations where misinformation can be knowingly or unknowingly spread. The problem with sharing and forwarding information on social media without fact-checking is that it usually starts in small, trusted networks before going on to be widely seen across the internet. This web which begins is infinite and cutting it from the roots is necessary. The rapid spread of information on social media is driven by algorithms that prioritise engagement and often they amplify misleading or false content and contribute to the spread of misinformation.  The algorithm optimises the feed and ensures that the posts that are most likely to engage with appear at the top of the timeline, thus encouraging a cycle of liking and posting that keeps users active and scrolling.

The internet reaches billions of individuals and enables them to tailor persuasive messages to the specific profiles of individual users. The internet because of its reach is an ideal medium for the fast spread of falsehoods at the expense of accurate information. 

Recommendations for Combating Passive Sharing

The need to combat passive sharing that we indulge in is important and some ways in which we can do so are as follows:

• We need to critically evaluate the sources before sharing any content. This will ensure that the information source is not corrupted and used as a means to cause disruptions. The medium should not be used to spread misinformation due to the source's ulterior motives. Tools such as crowdsourcing and AI methods have been used in the past to evaluate the sources and have been successful to an extent.
• Engaging with fact-checking tools and verifying the information is also crucial. The information that has been shared on the post needs to be verified through authenticated sources before indulging in the practice of sharing. 
• Being mindful of the potential impact of online activity, including likes and shares is important. The kind of reach that social media users have today is due to several reasons ranging from the content they create, the rate at which they engage with other users etc.  Liking and sharing content might not seem much for an individual user but the impact it has collectively is huge.

Conclusion 

Passive sharing of misinformation, like liking or sharing without verification, amplifies false information, erodes trust in legitimate sources, and deepens social and political divides. It can lead to real-world harm and ethical dilemmas. To combat this, critical evaluation, fact-checking, and mindful online engagement are essential to mitigating this passive spread of misinformation. The small act of “like” or “share” has a much more far-reaching effect than we anticipate and we should be mindful of all our activities on the digital platform. 

References

• https://www.tandfonline.com/doi/full/10.1080/00049530.2022.2113340#summary-abstract 
• https://timesofindia.indiatimes.com/city/thane/badlapur-protest-police-warn-against-spreading-fake-news/articleshow/112750638.cms

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Introduction

Misinformation poses a significant challenge to public health policymaking since it undermines efforts to promote effective health interventions and protect public well-being. The spread of inaccurate information, particularly through online channels such as social media and internet platforms, further complicates the decision-making process for policymakers since it perpetuates public confusion and distrust. This misinformation can lead to resistance against health initiatives, such as vaccination programs, and fuels scepticism towards scientifically-backed health guidelines.

Before the COVID-19 pandemic, misinformation surrounding healthcare largely encompassed the effects of alcohol and tobacco consumption, marijuana use, eating habits, physical exercise etc. However, there has been a marked shift in the years since. One such example is the outcry against palm oil in 2024: it is an ingredient prevalent in numerous food and cosmetic products, and came under the scanner after a number of claims that palmitic acid, which is present in palm oil, is detrimental to our health. However, scientific research by reputable institutions globally established that there is no cause for concern regarding the health risks posed by palmitic acid. Such trends and commentaries tend to create a parallel unscientific discourse that has the potential to not only impact individual choices but also public opinion and as a result, market developments and policy conversations. 

A prevailing narrative during the worst of the Covid-19 pandemic was that the virus had been engineered to control society and boost hospital profits. The extensive misinformation surrounding COVID-19 and its management and care increased vaccine hesitancy amongst people worldwide. It is worth noting that vaccine hesitancy has been a consistent trend historically; the World Health Organisation flagged vaccine hesitancy as one of the main threats to global health, and there have been other instances where a majority of the population refused to get vaccinated anticipating unverified, long-lasting side effects. For example, research from 2016 observed a significant level of public skepticism regarding the development and approval process of the Zika vaccine in Africa. Further studies emphasised the urgent need to disseminate accurate information about the Zika virus on online platforms to help curb the spread of the pandemic. 

In India during the COVID-19 pandemic, despite multiple official advisories, notifications and guidelines issued by the government and ICMR, people continued to remain opposed to vaccination, which resulted in inflated mortality rates within the country. Vaccination hesitancy was also compounded by anti-vaccination celebrities who claimed that vaccines were dangerous and contributed in large part to the conspiracy theories doing the rounds. Similar hesitation was noted in misinformation surrounding the MMR vaccines and their likely role in causing autism was examined.  At the time of the crisis, the Indian government also had to tackle disinformation-induced fraud surrounding the supply of oxygens in hospitals. Many critically-ill patients relied on fake news and unverified sources that falsely portrayed the availability of beds, oxygen cylinders and even home set-ups, only to be cheated out of money. 

The above examples highlight the difficulty health officials face in administering adequate healthcare. The special case of the COVID-19 pandemic also highlighted how current legal frameworks failed to address misinformation and disinformation, which impedes effective policymaking. It also highlights how taking corrective measures against health-related misinformation becomes difficult since such corrective action creates an uncomfortable gap in an individual’s mind, and it is seen that people ignore accurate information that may help bridge the gap. Misinformation, coupled with the infodemic trend, also leads to false memory syndrome, whereby people fail to differentiate between authentic information and fake narratives. Simple efforts to correct misperceptions usually backfire and even strengthen initial beliefs, especially in the context of complex issues like healthcare. Policymakers thus struggle with balancing policy making and making people receptive to said policies in the backdrop of their tendencies to reject/suspect authoritative action. Examples of the same can be observed on both the domestic front and internationally. In the US, for example, the traditional healthcare system rations access to healthcare through a combination of insurance costs and options versus out-of-pocket essential expenses. While this has been a subject of debate for a long time, it hadn’t created a large scale public healthcare crisis because the incentives offered to the medical professionals and public trust in the delivery of essential services helped balance the conversation. In recent times, however, there has been a narrative shift that sensationalises the system as an issue of deliberate “denial of care,” which has led to concerns about harms to patients.

Policy Recommendations

The hindrances posed by misinformation in policymaking are further exacerbated against the backdrop of policymakers relying on social media as a method to measure public sentiment, consensus and opinions. If misinformation about an outbreak is not effectively addressed, it could hinder individuals from adopting necessary protective measures and potentially worsen the spread of the epidemic. To improve healthcare policymaking amidst the challenges posed by health misinformation, policymakers must take a multifaceted approach. This includes convening a broad coalition of central, state, local, territorial, tribal, private, nonprofit, and research partners to assess the impact of misinformation and develop effective preventive measures. Intergovernmental collaborations such as the Ministry of Health and the Ministry of Electronics and Information Technology should be encouraged whereby doctors debunk online medical misinformation, in the backdrop of the increased reliance on online forums for medical advice. Furthermore, increasing investment in research dedicated to understanding misinformation, along with the ongoing modernization of public health communications, is essential. Enhancing the resources and technical support available to state and local public health agencies will also enable them to better address public queries and concerns, as well as counteract misinformation. Additionally, expanding efforts to build long-term resilience against misinformation through comprehensive educational programs is crucial for fostering a well-informed public capable of critically evaluating health information.

From an individual perspective, since almost half a billion people use WhatsApp it has become a platform where false health claims can spread rapidly. This has led to a rise in the use of fake health news. Viral WhatsApp messages containing fake health warnings can be dangerous, hence it is always recommended to check such messages with vigilance. This highlights the growing concern about the potential dangers of misinformation and the need for more accurate information on medical matters.

Conclusion

The proliferation of misinformation in healthcare poses significant challenges to effective policymaking and public health management. The COVID-19 pandemic has underscored the role of misinformation in vaccine hesitancy, fraud, and increased mortality rates. There is an urgent need for robust strategies to counteract false information and build public trust in health interventions; this includes policymakers engaging in comprehensive efforts, including intergovernmental collaboration, enhanced research, and public health communication modernization, to combat misinformation. By fostering a well-informed public through education and vigilance, we can mitigate the impact of misinformation and promote healthier communities.

References

1. van der Meer, T. G. L. A., & Jin, Y. (2019), “Seeking Formula for Misinformation Treatment in Public Health Crises: The Effects of Corrective Information Type and Source” Health Communication, 35(5), 560–575. https://doi.org/10.1080/10410236.2019.1573295 
2. “Health Misinformation”, U.S. Department of Health and Human Services. https://www.hhs.gov/surgeongeneral/priorities/health-misinformation/index.html 
3. Mechanic, David, “The Managed Care Backlash: Perceptions and Rhetoric in Health Care Policy and the Potential for Health Care Reform”, Rutgers University. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2751184/pdf/milq_195.pdf 
4. “Bad actors are weaponising health misinformation in India”, Financial Express, April 2024.

https://www.financialexpress.com/life/entertainment-bad-actors-are-weaponising-health-misinformation-in-india-3448871/ 

5. “Role of doctors in eradicating misinformation in the medical sector.”, Times of India, 1 July 2024. https://timesofindia.indiatimes.com/life-style/health-fitness/health-news/national-doctors-day-role-of-doctors-in-eradicating-misinformation-in-the-healthcare-sector/articleshow/111399098.cms 

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CAPTCHA, or the Completely Automated Public Turing Test to Tell Computers and Humans Apart function, is an image or distorted text that users have to identify or interpret to prove they are human. 2007 marked the inception of CAPTCHA, and Google developed its free service called reCAPTCHA, one of the most commonly used technologies to tell computers apart from humans. CAPTCHA protects websites from spam and abuse by using tests considered easy for humans but were supposed to be difficult for bots to solve. 

But, now this has changed. With AI becoming more and more sophisticated, it is now capable of solving CAPTCHA tests at a rate that is more accurate than humans, rendering them increasingly ineffective. This raises the question of whether CAPTCHA is still effective as a detection tool with the advancements of AI.

CAPTCHA Evolution: From 2007 Till Now

CAPTCHA has evolved through various versions to keep bots at bay. reCAPTCHA v1 relied on distorted text recognition, v2 introduced image-based tasks and behavioural analysis, and v3 operated invisibly, assigning risk scores based on user interactions. While these advancements improved user experience and security, AI now solves CAPTCHA with 96% accuracy, surpassing humans (50-86%). Bots can mimic human behaviour, undermining CAPTCHA’s effectiveness and raising the question: is it still a reliable tool for distinguishing real people from bots?

Smarter Bots and Their Rise

AI advancements like machine learning, deep learning and neural networks have developed at a very fast pace in the past decade, making it easier for bots to bypass CAPTCHA. They allow the bots to process and interpret the CAPTCHA types like text and images with almost human-like behaviour. Some examples of AI developments against bots are OCR or Optical Character Recognition. The earlier versions of CAPTCHA relied on distorted text: AI because of this tech is able to recognise and decipher the distorted text, making CAPTCHA useless. AI is trained on huge datasets which allows Image Recognition by identifying the objects that are specific to the question asked. These bots can mimic human habits and patterns by Behavioural Analysis and therefore fool the CAPTCHA. 

To defeat CAPTCHA, attackers have been known to use Adversarial Machine Learning, which refers to AI models trained specifically to defeat CAPTCHA. They collect CAPTCHA datasets and answers and create an AI that can predict correct answers. The implications that CAPTCHA failures have on platforms can range from fraud to spam to even cybersecurity breaches or cyberattacks. 

CAPTCHA vs Privacy: GDPR and DPDP

GDPR and the DPDP Act emphasise protecting personal data, including online identifiers like IP addresses and cookies. Both frameworks mandate transparency when data is transferred internationally, raising compliance concerns for reCAPTCHA, which processes data on Google’s US servers. Additionally, reCAPTCHA's use of cookies and tracking technologies for risk scoring may conflict with the DPDP Act's broad definition of data. The lack of standardisation in CAPTCHA systems highlights the urgent need for policymakers to reevaluate regulatory approaches.

CyberPeace Analysis: The Future of Human Verification

CAPTCHA, once a cornerstone of online security, is losing ground as AI outperforms humans in solving these challenges with near-perfect accuracy. Innovations like invisible CAPTCHA and behavioural analysis provided temporary relief, but bots have adapted, exploiting vulnerabilities and undermining their effectiveness. This decline demands a shift in focus. 

Emerging alternatives like AI-based anomaly detection, biometric authentication, and blockchain verification hold promise but raise ethical concerns like privacy, inclusivity, and surveillance. The battle against bots isn’t just about tools but it’s about reimagining trust and security in a rapidly evolving digital world.

AI is clearly winning the CAPTCHA war, but the real victory will be designing solutions that balance security, user experience and ethical responsibility. It’s time to embrace smarter, collaborative innovations to secure a human-centric internet.

References

• https://www.business-standard.com/technology/tech-news/bot-detection-no-longer-working-just-wait-until-ai-agents-come-along-124122300456_1.html 
• https://www.milesrote.com/blog/ai-defeating-recaptcha-the-evolving-battle-between-bots-and-web-security 
• https://www.technologyreview.com/2023/10/24/1081139/captchas-ai-websites-computing/‍
• https://datadome.co/guides/captcha/recaptcha-gdpr/