What are we going to do better? 

(Especially when lives depend on it)

 Robot and AI

Autonomous and assistive robots are growing routes into our way of living and effect how we interface with daily life. From warehouse to home sweepers, they are here. 

This year, Bert is being tested as one of Amazon’s first autonomous mobile robots, or AMRs. It’s designed to find its way safely through the company’s facilities on its own. In the future, a worker could summon a robot like Bert to carry heavy loads from one end of the warehouse to the other, cutting down on human wear-and-tear.

Construction robots are silhouettes in early morning light. 

CERT Documents

The Community Emergency Response Team (CERT) training is a national program to train citizens to help fill the gap between a disaster or emergency, and the arrival of professional services.

Some people are not purchasing the correct face masks for the current air quality situation. P99, N95,and N100 are the correct ones for Air Quality Alert Situations.

  • P99 – For Adults & Kids 
  • N95 – For Adults 

If you cannot find it online, please call (415) 488-5851 or email info@guardianairwaves.com. We have a limited supply that you can purchase from us.

The following do not protect your lungs from wildfire smoke:

  • Bandannas or towels (wet or dry) or tissue held over the mouth and nose. This may relieve dryness but won’t protect your lungs from wildfire smoke.
  • One‐strap paper dust mask or a surgical mask that hooks around your ears. These don’t protect against the fine particles in smoke.
  • For those who cannot avoid prolonged activities outdoors “Particulate respirator” masks (respirator masks) labeled N95 or N100 may provide some protection: they filter out fine particles but not hazardous gases ‒ The respirator masks do not seal well on people with facial hair or beards –
  • Individuals with respiratory conditions should consult their doctor before using a mask— masks may limit airflow and make it more difficult to breathe. ‒ Respirator masks should not be used on very young children: they don’t seal well enough to provide protection.
What can I do to protect myself?
  • Limiting exposure to wildfire smoke by remaining indoors is the primary goal. Depending on your situation, a combination of the strategies below may work best and give you the most protection from wildfire smoke.
  • Keep indoor air as clean as possible. Keep windows and doors closed.
  • Use a high-efficiency particulate air (HEPA) filter to reduce indoor air pollution.
  • Avoid smoking tobacco, using wood-burning stoves or fireplaces, burning candles, incenses or vacuuming.
  • Minimize the amount of time spent outdoors as much as possible. Avoid vigorous outdoor activities.
  • Drink plenty of water
  • Listen to your body and contact your healthcare provider or call 911 if you experience difficulty breathing, chest pain, severe fatigue, dizziness, or worsening of asthma or chronic respiratory illness.

A New Vision for Emergency Management

Date: Thu Mar 15 2018

Author: Brock Long, FEMA Administrator

Today I released FEMA’s 2018-2022 Strategic Plan, not just to guide FEMA as an Agency as we lead the way to a more resilient nation, but to serve as a strategy and an anchor for the whole community.

We cannot accomplish this by simply improving and expanding our programs and processes. We, as nation, must address some fundamental, cultural issues in order to become resilient. Resiliency is more than just strengthening our buildings and other infrastructure, it’s making sure that our citizens have the proper tools and skill sets to reduce the impact of future disasters.

This isn’t just our plan though; this plan will be a roadmap for the future of emergency management.

We as individuals need to get back to a “be prepared” mentality that served the nation through periods of both war and peace in the past, through periods of economic prosperity and during times of personal and national austerity. No matter how challenging the time, America has always been and will always be strongest when we ensure that our people are strong.

Embracing this culture of preparedness starts not in Washington, DC, but at home. We need to work to encourage everybody to question how prepared they are, and to act. Do you have CPR training? Do you know how to shut off the water valves and the gas valves in your home? Do you know what to do when a disaster strikes?

This journey does not begin and end at home, but moves out to spawn a culture where neighbor helping neighbor is not just a phrase or an idea, it is the reality. Citizens are the true first responders, so you need to be the help until help arrives.

Know your neighbors, and what they may need if a disaster happens. Build a support network in your community that includes preparing together and having a plan to check on each other after a disaster occurs. We are here to help you prepare and understand your risks, but a true culture of preparedness begins with you.

Part of being prepared is understanding your finances. Does your family have enough savings in case of an emergency? Alarmingly, almost 60 percent of all Americans don’t have $400 in savings. We as a nation need to address financial wellness as a building block of preparedness.  We need to double the amount of flood insurance coverage we have in the country because any home can flood, and everyone recovers more quickly when insured. Mother Nature doesn’t recognize flood zone maps, and we currently have too many people at risk. And it’s not just flood insurance, its insurance against high winds in hurricane and tornado-prone areas, and earthquake insurance to protect your investment. Everyone should have the right insurance coverage for the hazards you face.

Everyone – whether you are a public servant, a member of a family, or a business that is part of a community – must work together to make this happen, FEMA alone cannot accomplish these goals.

Now is the time for all of us to prepare and be ready for the next disaster, and to help make our neighbors, communities, and nation more resilient.

What are we going to do better? 

(Especially when lives depend on it)

 Robot and AI

Autonomous and assistive robots are growing routes into our way of living and effect how we interface with daily life. From warehouse to home sweepers, they are here. 

This year, Bert is being tested as one of Amazon’s first autonomous mobile robots, or AMRs. It’s designed to find its way safely through the company’s facilities on its own. In the future, a worker could summon a robot like Bert to carry heavy loads from one end of the warehouse to the other, cutting down on human wear-and-tear.

 

Construction robots are silhouettes in early morning light. Traditional tractor treads are being replaced with omni-directional wheels.

“Overtrust of Robots in Emergency Evacuation Scenarios,”

Paul Robinette, Wenchen Li, Robert Allen, Ayanna M. Howard, Alan R. Wagner

Georgia Tech Research Institute, Atlanta, GA, USA 2016

A research group at Georgia Tech Research Institute conducted an experiment that demonstrated that participants followed the evacuation instructions of a robot─even though half of the participants observed the same robot performing poorly in a navigation guidance task just minutes before. As AI systems become increasingly prevalent in our daily lives, how can we mitigate our inclination to overtrust these systems?

Ayanna Howard discusses her work in an interview with ACM: Based on ongoing research in my lab, we’ve continued to validate this human propensity for overtrust of AI. The emergency evacuation overtrust study was one of the earliest ones from the group to validate this phenomenon that emerged when humans interact with robotic systems that require them to make a quick decision under pressure. Since then, my group has made a number of other interesting findings, such as: 1) humans are more likely to rely on the AI if they need to make decisions concerning individuals that belong to a different demographic group (which links to our studies examining AI bias); 2) providing humans with more autonomy when asking for assistance further increases trust; and 3) a person’s positive or negative initial interactions with AI has a direct correlation to their ongoing trust in the system, irrespective of whether the AI is performing poorly or not. My research group has also continued to examine ways to mitigate this inclination to overtrust these systems. Although still preliminary, we’ve found that if we actively design distrust into the system, we can make it more safe. One methodology we’re exploring is tangentially linked to the field of explainable AI, where the system provides an explanation with respect to some of its risks or uncertainties. Given that all of these systems have uncertainty, we’ve begun designing our AI system to provide information concerning its uncertainty in a way that the human can understand, both at an emotional and cerebral level, in order to change their trust behavior.

Uncovered inherent biases in algorithms – 

I’m actually happy to say that my group published one of the earliest papers on recognizing inherent biases in algorithms. In fact, one of our papers on the biases found in emotion recognition algorithms was first published in 2017 and was titled “Addressing Bias in Machine Learning Algorithms: A Pilot Study on Emotion Recognition for Intelligent Systems,” where we examined the biases found in a commercial cloud-based emotion recognition system and proposed a solution that built upon it for improving the classification rate for the minority group while maintaining equivalent classification rates for the majority group. Since then, my research group has both uncovered biases in AI algorithms but also proposed solutions to mitigate those biases. Some of the solutions that can be taken to ensure fairer algorithms are societal and some are technical.

I believe that, as a field, we still need to tackle the general problem of underrepresentation in AI. As a community, we need to recognize that differences matter and that team diversity for designing solutions for a diverse world population is not just a nice-to-have, but a requisite. On the technical side, we need to design a form of AI accountability within our algorithms. We tend to be so focused on metrics such as accuracy, precision, recall, etc. that we disregard (or devalue) other metrics for quantifying algorithmic fairness, such as measuring disparate impact. As a community, we need to expand our metrics of performance to include fairness as a required metric rather than viewing it as a secondary post-processing criterion. – Ayanna Howard